Merge pull request #3874 from syncfusion-content/997029-smart-scheduler-images

997029 : Improved maui smart scheduler UG

Author: saiganesh-sakthivel

MAUI/SmartScheduler/claude-service.md

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+---
+layout: post
+title: Claude AI for AI-Powered Scheduler | Syncfusion®
+description: Learn how to implement a custom AI service using the Claude API with Syncfusion<sup>&reg;</sup> AI-Powered Scheduler (SfSmartScheduler) control.
+platform: maui
+control: SfSmartScheduler
+documentation: ug
+---
+
+# Claude AI Integration with .NET MAUI AI-Powered Scheduler
+
+The Syncfusion [.NET MAUI AI-Powered Scheduler] (SfSmartScheduler) can provide AI-powered suggestions while appointment scheduling. You can integrate Anthropic `Claude AI` using the `IChatInferenceService` interface, which acts as a bridge between the scheduler and your custom AI service.
+
+## Setting Up Claude
+
+1. **Create an Anthropic Account**  
+   Visit [Anthropic Console](https://console.anthropic.com), sign up, and complete the verification process.
+2. **Obtain an API Key**  
+   Navigate to [API Keys](https://console.anthropic.com/settings/keys) and click "Create Key."
+3. **Review Model Specifications**  
+   Refer to [Claude Models Documentation](https://docs.anthropic.com/claude/docs/models-overview) for details on available models.
+
+## Create a Claude AI Service
+
+This service handles communication with the Claude API, including authentication and response parsing.
+
+1. Create a `Services` folder in your project.
+2. Add a new file named `ClaudeAIService.cs` in the `Services` folder.
+3. Implement the service as shown below, storing the API key securely in a configuration file or environment variable (e.g., `appsettings.json`).
+
+{% tabs %}
+{% highlight c# tabtitle="ClaudeAIService.cs" %}
+
+using System.Net;
+using System.Text;
+using System.Text.Json;
+using Microsoft.Extensions.AI;
+
+public class ClaudeAIService
+{
+    private readonly string _apiKey;
+    private readonly string _modelName = "claude-3-5-sonnet-20241022"; // Example model
+    private readonly string _endpoint = "https://api.anthropic.com/v1/messages";
+    private static readonly HttpClient HttpClient = new(new SocketsHttpHandler
+    {
+        PooledConnectionLifetime = TimeSpan.FromMinutes(30),
+        EnableMultipleHttp2Connections = true
+    })
+    {
+        DefaultRequestVersion = HttpVersion.Version20 // Fallback to HTTP/2 for compatibility
+    };
+    private static readonly JsonSerializerOptions JsonOptions = new()
+    {
+        PropertyNamingPolicy = JsonNamingPolicy.CamelCase
+    };
+
+    public ClaudeAIService(IConfiguration configuration)
+    {
+        _apiKey = configuration["Claude:ApiKey"] ?? throw new ArgumentNullException("Claude API key is missing.");
+        if (!HttpClient.DefaultRequestHeaders.Contains("x-api-key"))
+        {
+            HttpClient.DefaultRequestHeaders.Clear();
+            HttpClient.DefaultRequestHeaders.Add("x-api-key", _apiKey);
+            HttpClient.DefaultRequestHeaders.Add("anthropic-version", "2023-06-01"); // Check latest version in Claude API docs
+        }
+    }
+
+    public async Task<string> CompleteAsync(List<ChatMessage> chatMessages)
+    {
+        var requestBody = new ClaudeChatRequest
+        {
+            Model = _modelName,
+            Max_tokens = 1000, // Maximum tokens in response
+            Messages = chatMessages.Select(m => new ClaudeMessage
+            {
+                Role = m.Role == ChatRole.User ? "user" : "assistant",
+                Content = m.Text
+            }).ToList(),
+            Stop_sequences  = new List<string> { "END_INSERTION", "NEED_INFO", "END_RESPONSE" } // Configurable stop sequences
+        };
+
+        var content = new StringContent(JsonSerializer.Serialize(requestBody, JsonOptions), Encoding.UTF8, "application/json");
+
+        try
+        {
+            var response = await HttpClient.PostAsync(_endpoint, content);
+            response.EnsureSuccessStatusCode();
+            var responseString = await response.Content.ReadAsStringAsync();
+            var responseObject = JsonSerializer.Deserialize<ClaudeChatResponse>(responseString, JsonOptions);
+            return responseObject?.Content?.FirstOrDefault()?.Text ?? "No response from Claude model.";
+        }
+        catch (Exception ex) when (ex is HttpRequestException || ex is JsonException)
+        {
+            throw new InvalidOperationException("Failed to communicate with Claude API.", ex);
+        }
+    }
+}
+
+{% endhighlight %}
+{% endtabs %}
+
+N> Store the Claude API key in `appsettings.json` (e.g., `{ "Claude": { "ApiKey": "your-api-key" } }`) or as an environment variable to ensure security. Verify the `anthropic-version` header in [Claude API Documentation](https://docs.anthropic.com/claude/docs) for the latest version.
+
+## Define Request and Response Models
+
+Create a file named `ClaudeModels.cs` in the Services folder and add:
+
+{% tabs %}
+{% highlight c# tabtitle="ClaudeModels.cs" %}
+
+public class ClaudeChatRequest
+{
+    public string? Model { get; set; }
+    public int Max_tokens { get; set; }
+    public List<ClaudeMessage>? Messages { get; set; }
+    public List<string>? Stop_sequences  { get; set; }
+}
+
+public class ClaudeMessage
+{
+    public string? Role { get; set; }
+    public string? Content { get; set; }
+}
+
+public class ClaudeChatResponse
+{
+    public List<ClaudeContentBlock>? Content { get; set; }
+}
+
+public class ClaudeContentBlock
+{
+    public string? Text { get; set; }
+}
+
+{% endhighlight %}
+{% endtabs %}
+
+## Implement IChatInferenceService
+
+Create `ClaudeInferenceService.cs`:
+
+{% tabs %}
+{% highlight c# tabtitle="ClaudeInferenceService.cs" %}
+
+using Syncfusion.Maui.SmartComponents;
+
+public class ClaudeInferenceService : IChatInferenceService
+{
+    private readonly ClaudeAIService _claudeService;
+
+    public ClaudeInferenceService(ClaudeAIService claudeService)
+    {
+        _claudeService = claudeService;
+    }
+
+    public async Task<string> GenerateResponseAsync(List<ChatMessage> chatMessages)
+    {
+        return await _claudeService.CompleteAsync(chatMessages);
+    }
+}
+
+{% endhighlight %}
+{% endtabs %}
+
+## Register Services in MAUI
+
+Update `MauiProgram.cs`:
+
+{% tabs %}
+{% highlight c# tabtitle="MauiProgram.cs" hl_lines="9 10" %}
+
+using Syncfusion.Maui.Core.Hosting;
+using Syncfusion.Maui.SmartComponents;
+
+var builder = MauiApp.CreateBuilder();
+builder
+    .UseMauiApp<App>()
+    .ConfigureSyncfusionCore();
+
+builder.Services.AddSingleton<ClaudeAIService>();
+builder.Services.AddSingleton<IChatInferenceService, ClaudeInferenceService>();
+
+
+{% endhighlight %}
+{% endtabs %}

MAUI/SmartScheduler/custom-ai-service.md

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+---
+layout: post
+title: Custom AI for AI-Powered Scheduler control | Syncfusion®
+description: Learn how to use IChatInferenceService to integrate custom AI services with Syncfusion® .NET MAUI AI-Powered Scheduler (SfSmartScheduler) control
+platform: maui
+control: SfSmartScheduler
+documentation: ug
+---
+
+# Custom AI Service Integration with .NET MAUI AI-Powered Scheduler
+
+The Syncfusion .NET MAUI AI-Powered Scheduler can use AI to provide intelligent suggestions while scheduling appointments. By default, it works with providers like `OpenAI` or `Azure OpenAI` or `Ollama`, but you can also integrate your own AI service using the `IChatInferenceService` interface. This interface ensures smooth communication between the AI-Powered Scheduler and your custom AI logic.
+
+## IChatInferenceService Interface
+
+The `IChatInferenceService` interface defines how the AI-Powered Scheduler interacts with an AI service. It sends user input and context messages and expects an AI-generated response.
+
+{% tabs %}
+{% highlight xaml tabtitle="C#" %}
+
+using Syncfusion.Maui.SmartComponents;
+
+Public interface IChatInferenceService
+{
+    Task<string> GenerateResponseAsync(List<ChatMessage> chatMessages);
+}
+
+{% endhighlight %}
+{% endtabs %}
+
+- **Purpose**: Provides a standard way to connect any AI service.
+- **Parameter**: The `chatMessages` contains the user’s text and previous context.
+- **Benefit**: Lets you switch AI providers without changing the editor code.
+
+## Custom AI Service Implementation
+
+Here’s a simple example of a mock AI service that implements `IChatInferenceService`. You can replace the logic with your own AI integration:
+
+{% tabs %}
+{% highlight xaml tabtitle="C#" %}
+
+using Microsoft.Extensions.AI;
+using Syncfusion.Maui.SmartComponents;
+
+public class MockAIService : IChatInferenceService
+{
+    public Task<string> GenerateResponseAsync(List<ChatMessage> chatMessages);
+    {
+
+    }
+}
+
+{% endhighlight %}
+{% endtabs %}
+
+## Registering the Custom AI Service
+
+Register the custom AI service in **MauiProgram.cs**:
+
+{% tabs %}
+{% highlight xaml tabtitle="C#" %}
+
+using Syncfusion.Maui.Core.Hosting;
+using Syncfusion.Maui.SmartComponents;
+
+var builder = MauiApp.CreateBuilder()
+....
+
+builder.Services.AddSingleton<IChatInferenceService, MockAIService>();
+
+{% endhighlight %}
+{% endtabs %}
+
+## How to test Custom AI Integration
+
+1. Implement and register your custom AI service.
+2. Add SfSmartScheduler to your page.
+3. Run the app and start using assist view.
+4. Check if suggestions appear based on your AI logic.
+
+## Implemented AI Services
+
+Here are examples of AI services integrated using the `IChatInferenceService` interface:
+
+| Service | Documentation |
+|---------|---------------|
+| Claude | [Claude Integration](claude-service) |
+| DeepSeek | [DeepSeek Integration](deepseek-service) |
+| Groq | [Groq Integration](groq-service) |
+| Gemini | [Gemini Integration](gemini-service) |
+
+## Troubleshooting
+
+If the custom AI service does not work as expected, try the following:
+- **No Suggestions Displayed**: Ensure the `IChatInferenceService` implementation is registered in **MauiProgram.cs** and returns valid responses. Check for errors in the `GenerateResponseAsync` method.