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Claude AI Integration with Blazor Smart TextArea

16 Oct 202510 minutes to read

The Syncfusion Blazor Smart TextArea component provides AI-powered autocompletion for context-aware text input, typically using OpenAI or Azure OpenAI. This guide explains how to integrate the Anthropic Claude AI service with the Smart TextArea using the IChatInferenceService interface, enabling custom AI-driven responses in a Blazor Web App.

Setting Up Claude

  1. Create an Anthropic Account
    Visit Anthropic Console, sign up, and complete the verification process.
  2. Obtain an API Key
    Navigate to API Keys and click “Create Key.”
  3. Review Model Specifications
    Refer to Claude Models Documentation for details on available models.

Create a Claude AI Service

Create a service class to manage interactions with the Claude API, including authentication and response processing for the Smart TextArea.

  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).
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(IList<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);
        }
    }
}

NOTE

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 for the latest version.

Define Request and Response Models

Define C# classes to match the Claude API’s JSON request and response format.

  1. Create a new file named ClaudeModels.cs in the Services folder.
  2. Add the following model classes:
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; }
}

Create a Custom AI Service

Implement the IChatInferenceService interface to connect the Smart TextArea to the Claude service, acting as a bridge for AI-generated responses.

  1. Create a new file named ClaudeInferenceService.cs in the Services folder.
  2. Add the following implementation:
using Syncfusion.Blazor.AI;
using System.Threading.Tasks;

public class ClaudeInferenceService : IChatInferenceService
{
    private readonly ClaudeAIService _claudeService;

    public ClaudeInferenceService(ClaudeAIService claudeService)
    {
        _claudeService = claudeService;
    }

    public async Task<string> GenerateResponseAsync(ChatParameters options)
    {
        return await _claudeService.CompleteAsync(options.Messages);
    }
}

Configure the Blazor App

Register the Claude service and IChatInferenceService implementation in the dependency injection container.

Update the ~/Program.cs file as follows:

using Microsoft.AspNetCore.Components;
using Microsoft.AspNetCore.Components.Web;
using Syncfusion.Blazor;
using Syncfusion.Blazor.AI;

var builder = WebApplication.CreateBuilder(args);

builder.Services.AddRazorPages();
builder.Services.AddServerSideBlazor();
builder.Services.AddSyncfusionBlazor();
builder.Services.AddSyncfusionSmartComponents();
builder.Services.AddSingleton<ClaudeAIService>();
builder.Services.AddSingleton<IChatInferenceService, ClaudeInferenceService>();

var app = builder.Build();
// ...

Use Claude AI with Smart TextArea

Add the Smart TextArea component to a Razor file (e.g., ~/Pages/Home.razor) to use Claude AI for autocompletion:

@using Syncfusion.Blazor.SmartComponents

<SfSmartTextArea UserRole="@userRole" UserPhrases="@userPhrases" Placeholder="Enter your queries here" @bind-Value="prompt" Width="75%" RowCount="5">
</SfSmartTextArea>

@code {
    private string? prompt;
    // Defines the context for AI autocompletion
    private string userRole = "Customer support representative";
    // Predefined phrases for AI to suggest during typing
    private string[] userPhrases = [
        "Thank you for reaching out.",
        "Please provide more details.",
        "We are investigating your issue."
    ];
}

Test the Integration

  1. Ensure all services are registered in Program.cs and the Smart TextArea is added to a Razor file.
  2. Run the application using Ctrl+F5 (Windows) or ⌘+F5 (macOS).
  3. Type phrases like “Thank” or “Please provide” in the Smart TextArea to verify that Claude AI generates appropriate suggestions.
  4. Check that suggestions appear as configured (e.g., inline or pop-up, based on the ShowSuggestionOnPopup setting).

Smart TextArea with Claude AI

Troubleshooting

If the Claude AI integration does not work, try the following:

  • No Suggestions Displayed: Verify that the Claude API key and model name are correct in the configuration. Check the ClaudeAIService implementation for errors.
  • HTTP Request Failures: Ensure a stable internet connection and that the Claude API endpoint (https://api.anthropic.com/v1/messages) is accessible. Test with HTTP/2 if compatibility issues arise.
  • Service Registration Errors: Confirm that ClaudeAIService and ClaudeInferenceService are registered in Program.cs.

See Also