DeepSeek AI Integration with ASP.NET Core Smart TextArea

14 May 20269 minutes to read

The Syncfusion ASP.NET Core Smart TextArea control provides AI-powered autocompletion for context-aware text input, typically using OpenAI or Azure OpenAI. This guide explains how to integrate the DeepSeek AI service with the Smart TextArea using the IChatInferenceService interface, enabling custom AI-driven responses in a ASP.NET Core App.

Setting Up DeepSeek

Obtain a DeepSeek API Key
Create an account at DeepSeek Platform, sign in, and navigate to API Keys to generate an API key.
Review Model Specifications
Refer to DeepSeek Models Documentation for details on available models (e.g., deepseek-chat).

Create a DeepSeek AI Service

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

Create a Services folder in your project.
Add a new file named DeepSeekAIService.cs in the Services folder.
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 DeepSeekAIService
{
    private readonly string _apiKey;
    private readonly string _modelName = "deepseek-chat"; // Example model
    private readonly string _endpoint = "https://api.deepseek.com/chat/completions";
    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 DeepSeekAIService(IConfiguration configuration)
    {
        _apiKey = configuration["DeepSeek:ApiKey"] ?? throw new ArgumentNullException("DeepSeek API key is missing.");
        if (!HttpClient.DefaultRequestHeaders.Contains("Authorization"))
        {
            HttpClient.DefaultRequestHeaders.Clear();
            HttpClient.DefaultRequestHeaders.Add("Authorization", $"Bearer {_apiKey}");
        }
    }

    public async Task<string> CompleteAsync(IList<ChatMessage> chatMessages)
    {
        var requestBody = new DeepSeekChatRequest
        {
            Model = _modelName,
            Temperature = 0.7f, // Controls response randomness (0.0 to 1.0)
            Messages = chatMessages.Select(m => new DeepSeekMessage
            {
                Role = m.Role == ChatRole.User ? "user" : "system", // Align with DeepSeek API roles
                Content = m.Text
            }).ToList()
        };

        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<DeepSeekChatResponse>(responseString, JsonOptions);
            return responseObject?.Choices?.FirstOrDefault()?.Message?.Content ?? "No response from DeepSeek.";
        }
        catch (Exception ex) when (ex is HttpRequestException || ex is JsonException)
        {
            throw new InvalidOperationException("Failed to communicate with DeepSeek API.", ex);
        }
    }
}

NOTE

Store the DeepSeek API key in appsettings.json (e.g., { "DeepSeek": { "ApiKey": "your-api-key" } }) or as an environment variable to ensure security.

Define Request and Response Models

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

Create a new file named DeepSeekModels.cs in the Services folder.
Add the following model classes:

public class DeepSeekMessage
{
    public string Role { get; set; }
    public string Content { get; set; }
}

public class DeepSeekChatRequest
{
    public string Model { get; set; }
    public float Temperature { get; set; }
    public List<DeepSeekMessage> Messages { get; set; }
}

public class DeepSeekChatResponse
{
    public List<DeepSeekChoice> Choices { get; set; }
}

public class DeepSeekChoice
{
    public DeepSeekMessage Message { get; set; }
}

Create a Custom AI Service

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

Create a new file named DeepSeekInferenceService.cs in the Services folder.
Add the following implementation:

using Syncfusion.EJ2.AI;
using System.Threading.Tasks;

public class DeepSeekInferenceService : IChatInferenceService
{
    private readonly DeepSeekAIService _deepSeekService;

    public DeepSeekInferenceService(DeepSeekAIService deepSeekService)
    {
        _deepSeekService = deepSeekService;
    }

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

Configure the ASP.NET Core App

Update the ~/Program.cs file as follows:

using Syncfusion.EJ2;
using Syncfusion.EJ2.AI;

var builder = WebApplication.CreateBuilder(args);

builder.Services.AddRazorPages();
builder.Services.AddSyncfusionSmartComponents();
builder.Services.AddSingleton<DeepSeekAIService>();
builder.Services.AddSingleton<IChatInferenceService, DeepSeekInferenceService>();

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

Add ASP.NET Core Smart TextArea Control

Add the Smart TextArea in the ~/Pages/Index.cshtml file to test the DeepSeek AI integration.

CSHTML
@{
    var presets = new { 
        userRole = "Maintainer of an open-source project replying to GitHub issues",
        userPhrases = new[] { "Thank you for contacting us.", "To investigate, we'll need a repro as a public Git repo.", "Could you please post a screenshot of NEED_INFO?", "This sounds like a usage question. This issue tracker is intended for bugs and feature proposals. Unfortunately, we don't have the capacity to answer general usage questions and would recommend StackOverflow for a faster response.", "We don't accept ZIP files as repros." }, 
        placeHolder = "Write your response to the GitHub issue..." };
}

<ejs-smarttextarea id="smartTextarea" user-role="@presets.userRole" user-phrases="@presets.userPhrases" width="75%" placeholder="@presets.placeHolder" floatLabelType="Auto" rows="5"></ejs-smarttextarea>

Press Ctrl+F5 (Windows) or ⌘+F5 (macOS) to run the app. Then, the Syncfusion^® ASP.NET Core
Smart TextArea control will be rendered in the default web browser.

ASP.NET Core Smart TextArea Control

Troubleshooting

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

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

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