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‎blazor-toc.html‎

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</ul>
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</li>
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</ul>
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<ul>
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<li>Tree Grid
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<ul>
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<li><a href="/blazor/smart-ai-solutions/ai-samples/treegrid/adaptive-structuring">Adaptive Structuring</a></li>
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</ul>
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</li>
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</ul>
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</li>
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<li>AI AssistView
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<ul>

‎blazor/smart-ai-solutions/ai-samples/treegrid/adaptive-structuring.md‎

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---
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layout: post
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title: Data Restructuring with Blazor TreeGrid and AI Models | Syncfusion
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description: Learn how to use Syncfusion Blazor TreeGrid with AI service to automatically organize hierarchical data.
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platform: Blazor
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control: AI Integration
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documentation: ug
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keywords: Blazor TreeGrid, AI data restructuring, Syncfusion Blazor AI
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---
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# Data Restructuring with Blazor TreeGrid and Ollama
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This guide demonstrates how to use the [**Syncfusion.Blazor.AI**](https://www.nuget.org/packages/Syncfusion.Blazor.AI) package to automatically organize hierarchical data in a Syncfusion Blazor TreeGrid component. The [**Syncfusion.Blazor.AI**](https://www.nuget.org/packages/Syncfusion.Blazor.AI) package enables integration with AI models to process and structure data, while Ollama provides self-hosted or cloud-based AI capabilities for analyzing relationships in datasets. In this example, the application assigns appropriate `ParentId` values based on `CategoryName` relationships, dynamically updating the TreeGrid to reflect the corrected hierarchical structure.
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## Prerequisites
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Ensure the following NuGet packages are installed based on your chosen AI service:
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### For OpenAI
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- **Microsoft.Extensions.AI**
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- **Microsoft.Extensions.AI.OpenAI**
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### For Azure OpenAI
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- **Microsoft.Extensions.AI**
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- **Microsoft.Extensions.AI.OpenAI**
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- **Azure.AI.OpenAI**
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### For Ollama
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- **Microsoft.Extensions.AI**
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- **OllamaSharp**
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{% tabs %}
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{% highlight C# tabtitle="Package Manager" %}
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Install-Package Syncfusion.Blazor.TreeGrid -Version {{ site.releaseversion }}
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Install-Package Syncfusion.Blazor.Themes -Version {{ site.releaseversion }}
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Install-Package Syncfusion.Blazor.AI -Version {{ site.releaseversion }}
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Install-Package Microsoft.Extensions.AI
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Install-Package Microsoft.Extensions.AI.OpenAI # For OpenAI or Azure OpenAI
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Install-Package Azure.AI.OpenAI # For Azure OpenAI
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Install-Package OllamaSharp # For Ollama
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{% endhighlight %}
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{% endtabs %}
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## Add Stylesheet and Script Resources
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Include the theme stylesheet and script from NuGet via [Static Web Assets](https://blazor.syncfusion.com/documentation/appearance/themes#static-web-assets) in the `<head>` of your main page:
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- For **.NET 6** Blazor Server apps, add to **~/Pages/_Layout.cshtml**.
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- For **.NET 8 or .NET 9** Blazor Server apps, add to **~/Components/App.razor**.
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```html
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<head>
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<link href="_content/Syncfusion.Blazor.Themes/tailwind.css" rel="stylesheet" />
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</head>
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<body>
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<script src="_content/Syncfusion.Blazor.Core/scripts/syncfusion-blazor.min.js" type="text/javascript"></script>
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</body>
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```
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N> Explore the [Blazor Themes](https://blazor.syncfusion.com/documentation/appearance/themes) topic for methods to reference themes ([Static Web Assets](https://blazor.syncfusion.com/documentation/appearance/themes#static-web-assets), [CDN](https://blazor.syncfusion.com/documentation/appearance/themes#cdn-reference), or [CRG](https://blazor.syncfusion.com/documentation/common/custom-resource-generator)). Refer to the [Adding Script Reference](https://blazor.syncfusion.com/documentation/common/adding-script-references) topic for different approaches to adding script references in your Blazor application.
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## Configure AI Service
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Choose one of the following AI services (OpenAI, Azure OpenAI, or Ollama) based on your requirements:
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- **OpenAI**: Best for cloud-based, general-purpose AI models with minimal setup.
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- **Azure OpenAI**: Ideal for enterprise-grade deployments with enhanced security and scalability.
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- **Ollama**: Suitable for self-hosted, privacy-focused AI models.
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Follow the instructions for your selected service to register the AI model in your application.
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### OpenAI
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Generate an API key from OpenAI and set `openAIApiKey`. Specify the desired model (e.g., `gpt-3.5-turbo`, `gpt-4`) in `openAIModel`.
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- Install the required NuGet packages:
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{% tabs %}
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{% highlight C# tabtitle="Package Manager" %}
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Install-Package Microsoft.Extensions.AI
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Install-Package Microsoft.Extensions.AI.OpenAI
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{% endhighlight %}
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{% endtabs %}
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- Add the following to the **~/Program.cs** file in your Blazor WebApp:
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{% tabs %}
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{% highlight C# tabtitle="Blazor WebApp" hl_lines="7 8 9 11 12 13" %}
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using Syncfusion.Blazor.AI;
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using Microsoft.Extensions.AI;
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using OpenAI;
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var builder = WebApplication.CreateBuilder(args);
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string openAIApiKey = "API-KEY";
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string openAIModel = "OPENAI_MODEL";
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OpenAIClient openAIClient = new OpenAIClient(openAIApiKey);
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IChatClient openAIChatClient = openAIClient.GetChatClient(openAIModel).AsIChatClient();
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builder.Services.AddChatClient(openAIChatClient);
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builder.Services.AddSingleton<IChatInferenceService, SyncfusionAIService>();
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var app = builder.Build();
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{% endhighlight %}
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{% endtabs %}
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### Azure OpenAI
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Deploy an Azure OpenAI Service resource and model as described in [Microsoft's documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource). Obtain values for `azureOpenAIKey`, `azureOpenAIEndpoint`, and `azureOpenAIModel`.
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- Install the required NuGet packages:
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{% tabs %}
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{% highlight C# tabtitle="Package Manager" %}
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Install-Package Microsoft.Extensions.AI
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Install-Package Microsoft.Extensions.AI.OpenAI
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Install-Package Azure.AI.OpenAI
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{% endhighlight %}
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{% endtabs %}
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- Add the following to the **~/Program.cs** file in your Blazor WebApp:
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{% tabs %}
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{% highlight C# tabtitle="Blazor WebApp" hl_lines="7 8 9 11 12 13" %}
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using Syncfusion.Blazor.AI;
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using Azure.AI.OpenAI;
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using Microsoft.Extensions.AI;
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using System.ClientModel;
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var builder = WebApplication.CreateBuilder(args);
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string azureOpenAIKey = "AZURE_OPENAI_KEY";
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string azureOpenAIEndpoint = "AZURE_OPENAI_ENDPOINT";
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string azureOpenAIModel = "AZURE_OPENAI_MODEL";
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AzureOpenAIClient azureOpenAIClient = new AzureOpenAIClient(
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new Uri(azureOpenAIEndpoint),
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new ApiKeyCredential(azureOpenAIKey)
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);
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IChatClient azureOpenAIChatClient = azureOpenAIClient.GetChatClient(azureOpenAIModel).AsIChatClient();
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builder.Services.AddChatClient(azureOpenAIChatClient);
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builder.Services.AddSingleton<IChatInferenceService, SyncfusionAIService>();
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var app = builder.Build();
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{% endhighlight %}
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{% endtabs %}
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### Ollama
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To use Ollama for self-hosted AI models:
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1. **Download and install Ollama**: Visit [Ollama's official website](https://ollama.com) and install the application for your operating system.
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2. **Install a model**: Choose a model from the [Ollama Library](https://ollama.com/library) (e.g., `llama2:13b`, `mistral:7b`).
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3. **Configure the application**: Provide the `Endpoint` URL (e.g., `http://localhost:11434`) and `ModelName` (e.g., `llama2:13b`).
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- Install the required NuGet packages:
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{% tabs %}
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{% highlight C# tabtitle="Package Manager" %}
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Install-Package Microsoft.Extensions.AI
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Install-Package OllamaSharp
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{% endhighlight %}
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{% endtabs %}
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- Add the following to the **~/Program.cs** file in your Blazor WebApp:
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{% tabs %}
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{% highlight C# tabtitle="Blazor WebApp" hl_lines="7 8 9 11 12 13" %}
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using Syncfusion.Blazor.AI;
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using Microsoft.Extensions.AI;
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using OllamaSharp;
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var builder = WebApplication.CreateBuilder(args);
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string ModelName = "MODEL_NAME";
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IChatClient chatClient = new OllamaApiClient("http://localhost:11434", ModelName);
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builder.Services.AddChatClient(chatClient);
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builder.Services.AddSingleton<IChatInferenceService, SyncfusionAIService>();
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var app = builder.Build();
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{% endhighlight %}
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{% endtabs %}
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- **Verify connectivity**: Ensure the Ollama server is running and accessible at the specified endpoint (e.g., `http://localhost:11434`) before starting the application.
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## Register Syncfusion Blazor Service
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Add the Syncfusion Blazor service to your **~/Program.cs** file. The configuration depends on your app's **Interactive Render Mode**:
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- **Server Mode**: Register the service in the single **~/Program.cs** file.
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- **WebAssembly or Auto Mode**: Register the service in both the server-side **~/Program.cs** and client-side **~/Program.cs** files.
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{% tabs %}
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{% highlight C# tabtitle="Server (~/_Program.cs)" hl_lines="3 11" %}
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using Syncfusion.Blazor;
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var builder = WebApplication.CreateBuilder(args);
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builder.Services.AddRazorComponents()
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.AddInteractiveServerComponents()
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.AddInteractiveWebAssemblyComponents();
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builder.Services.AddSyncfusionBlazor();
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var app = builder.Build();
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{% endhighlight %}
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{% highlight C# tabtitle="Client (~/_Program.cs)" hl_lines="2 5" %}
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using Syncfusion.Blazor;
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var builder = WebAssemblyHostBuilder.CreateDefault(args);
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builder.Services.AddSyncfusionBlazor();
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await builder.Build().RunAsync();
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{% endhighlight %}
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{% endtabs %}
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## Razor Component (`Home.razor`)
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This section implements the Syncfusion Blazor TreeGrid with AI-driven data restructuring using the AI model to assign `ParentId` values based on `CategoryName` relationships.
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```csharp
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@page "/"
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@inject IChatInferenceService AIService
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@using Syncfusion.Blazor.TreeGrid
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@using Syncfusion.Blazor.Navigations
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@using Syncfusion.Blazor.Buttons
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@using Syncfusion.Blazor.AI
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@using System.Text.Json;
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<div style="padding-bottom: 10px;">
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<span>@message</span>
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</div>
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<div style="width: 100%; position: relative">
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<SfTreeGrid @ref="TreeGrid" DataSource="@TreeGridData" IdMapping="CategoryId" ParentIdMapping="ParentId" TreeColumnIndex="1">
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<TreeGridEditSettings AllowEditing="true" />
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<TreeGridColumns>
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<TreeGridColumn Field="CategoryId" HeaderText="Category ID" IsPrimaryKey="true" Width="60" TextAlign="Syncfusion.Blazor.Grids.TextAlign.Right"></TreeGridColumn>
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<TreeGridColumn Field="CategoryName" HeaderText="Category Name" Width="100"></TreeGridColumn>
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<TreeGridColumn Field="Status" HeaderText="Status" Width="70"></TreeGridColumn>
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<TreeGridColumn Field="OrderDate" HeaderText="Last Order Date" Format="d" Width="90"></TreeGridColumn>
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</TreeGridColumns>
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<SfToolbar ID="TreeGrid_AISample_Toolbar">
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<ToolbarItems>
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<ToolbarItem>
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<Template>
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<SfButton IsPrimary ID="openAI" @onclick="OpenAIHandler">Smart Data Restructure</SfButton>
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</Template>
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</ToolbarItem>
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</ToolbarItems>
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</SfToolbar>
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</SfTreeGrid>
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</div>
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```
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`Home.razor.cs`
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```csharp
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using Microsoft.Extensions.AI;
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using Syncfusion.Blazor.AI;
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using Syncfusion.Blazor.TreeGrid;
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using System.Text.Json;
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namespace AISamples.Components.Pages
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{
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public partial class Home
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{
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public SfTreeGrid<TreeData.BusinessObject> TreeGrid;
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private string AIPrompt = string.Empty;
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private string message = string.Empty;
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public List<TreeData.BusinessObject> TreeGridData { get; set; }
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protected override void OnInitialized()
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{
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this.TreeGridData = TreeData.GetAdaptiveStructureData().ToList();
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}
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private async Task OpenAIHandler()
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{
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await TreeGrid.ShowSpinnerAsync();
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List<TreeData.BusinessObject> sortedCollection = new List<TreeData.BusinessObject>();
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var AIPrompt = GeneratePrompt(TreeGridData);
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ChatParameters chatParameters = new ChatParameters
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{
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Messages = new List<ChatMessage>
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{
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new ChatMessage(ChatRole.User, AIPrompt)
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}
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};
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var result = await AIService.GenerateResponseAsync(chatParameters);
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result = result.Replace("```json", "").Replace("```", "").Trim();
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string response = JsonDocument.Parse(result).RootElement.GetProperty("TreeGridData").ToString();
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if (response is not null)
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{
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sortedCollection = JsonSerializer.Deserialize<List<TreeData.BusinessObject>>(response);
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}
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if (sortedCollection is not null && sortedCollection.Count > 0)
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{
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TreeGridData = sortedCollection.Cast<TreeData.BusinessObject>().ToList();
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}
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else
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{
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message = "Oops.! Please try Again !";
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}
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await TreeGrid.HideSpinnerAsync();
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await Task.CompletedTask;
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}
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private string GeneratePrompt(List<TreeData.BusinessObject> TreeGridData)
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{
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Dictionary<string, IEnumerable<object>> treeData = new Dictionary<string, IEnumerable<object>>();
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treeData.Add("TreeGridData", TreeGridData);
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var jsonData = JsonSerializer.Serialize(treeData);
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return @"I want you to act as a TreeGrid Data Organizer.
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Your task is to organize a dataset based on a hierarchical structure using 'CategoryId' and 'ParentId'.
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Each item in the dataset has a 'CategoryName' representing categories, and some categories have a null 'ParentId', indicating they are top-level categories.
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Your role will be to examine the entire dataset to identify related items based on their 'CategoryName' values and nest them under the appropriate top-level categories by updating their 'ParentId' to match the 'CategoryId' of the corresponding top-level category.
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For example, if a category like 'Furniture' exists, you should examine the dataset for items such as 'Chair' and 'Table' and update their 'ParentId' to the 'CategoryId' of 'Furniture'.
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The output should be the newly prepared TreeGridData with correctly assigned 'ParentId' values. Please ensure that all subcategories are correctly nested under their respective top-level categories.
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Return the newly prepared TreeGridData alone and don't share any other information with the response: Here is the dataset " + jsonData + "/n Note: Return response must be in json string and with no other explanation. ";
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}
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public class TreeData
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{
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public class BusinessObject
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{
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public int CategoryId { get; set; }
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public string CategoryName { get; set; }
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public string Status { get; set; }
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public DateTime OrderDate { get; set; }
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public int? ParentId { get; set; }
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}
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public static List<BusinessObject> GetAdaptiveStructureData()
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{
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List<BusinessObject> BusinessObjectCollection = new List<BusinessObject>();
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 1, CategoryName = "Electronics", Status = "Available", OrderDate = new DateTime(2021, 7, 12), ParentId = null });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 2, CategoryName = "Cell phone", Status = "out of Stock", OrderDate = new DateTime(2021, 6, 17), ParentId = 1 });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 3, CategoryName = "Computer", Status = "Available", OrderDate = new DateTime(2021, 7, 12), ParentId = 7 });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 4, CategoryName = "Cloth", Status = "Available", OrderDate = new DateTime(2021, 10, 5), ParentId = null });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 5, CategoryName = "Silk", Status = "Out of Stock", OrderDate = new DateTime(2021, 9, 2), ParentId = 7 });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 6, CategoryName = "Chair", Status = "Available", OrderDate = new DateTime(2021, 3, 3), ParentId = 1 });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 7, CategoryName = "Furniture", Status = "Available", OrderDate = new DateTime(2021, 3, 5), ParentId = null });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 8, CategoryName = "Bed", Status = "Available", OrderDate = new DateTime(2021, 3, 5), ParentId = 7 });
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BusinessObjectCollection.Add(new BusinessObject() { CategoryId = 9, CategoryName = "Fabrics", Status = "Available", OrderDate = new DateTime(2021, 10, 5), ParentId = 4 });
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return BusinessObjectCollection;
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}
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}
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}
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}
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```
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## Error Handling and Troubleshooting
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If the AI service fails to return a valid response, the TreeGrid will display an error message ("Oops! Please try again!"). Common issues include:
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- **Invalid API Key or Endpoint**: Verify that the `openAIApiKey`, `azureOpenAIKey`, or Ollama `Endpoint` is correct and the service is accessible.
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- **Model Unavailable**: Ensure the specified `openAIModel`, `azureOpenAIModel`, or `ModelName` is deployed and supported.
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- **Network Issues**: Check connectivity to the AI service endpoint, especially for self-hosted Ollama instances.
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- **Large Datasets**: Processing large datasets may cause timeouts. Consider batching data or optimizing the prompt for efficiency.
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## Performance Considerations
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When handling large datasets, ensure the Ollama server has sufficient resources (CPU/GPU) to process requests efficiently. For datasets exceeding 10,000 records, consider splitting the data into smaller batches to avoid performance bottlenecks. Test the application with your specific dataset to determine optimal performance.
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## Sample Code
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A complete working example is available in the [Syncfusion Blazor AI Samples GitHub repository](https://github.com/syncfusion/smart-ai-samples).
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![Smart Structuring - Output](../../ai/images/adaptive-datastructuring.gif)

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