【.NET实战】调用DeepSeek API实现类官网的智能问答交互

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Bart_Lu

1077人浏览 · 2025-03-17 10:03:39

Bart_Lu · 2025-03-17 10:03:39 发布

一、场景与效果预览

通过.NET 6+开发Web应用，集成DeepSeek大模型API，实现以下效果：

用户输入问题后实时获取AI回答
对话式UI布局（类似官网）
流式响应效果（逐字输出）
支持历史对话记录

二、核心实现步骤

1. 准备工作

注册DeepSeek开发者账号并获取API Key
创建ASP.NET Core Web应用

安装NuGet包：

Install-Package System.Net.Http.Json
Install-Package Microsoft.Extensions.Http

2. 配置API服务

Program.cs 添加HttpClient服务：

csharp

builder.Services.AddHttpClient("DeepSeek", client => {
    client.BaseAddress = new Uri("https://api.deepseek.com/v1/");
    client.DefaultRequestHeaders.Authorization = 
        new AuthenticationHeaderValue("Bearer", builder.Configuration["DeepSeek:ApiKey"]);
});

3. 实现问答服务

创建DeepSeekService.cs：

public class DeepSeekService
{
    private readonly IHttpClientFactory _httpClientFactory;

    public DeepSeekService(IHttpClientFactory httpClientFactory)
    {
        _httpClientFactory = httpClientFactory;
    }

    public async Task<string> GetAnswerAsync(string question)
    {
        var client = _httpClientFactory.CreateClient("DeepSeek");
        
        var request = new {
            model = "deepseek-chat",
            messages = new[] {
                new { role = "user", content = question }
            },
            stream = true
        };

        var response = await client.PostAsJsonAsync("chat/completions", request);
        response.EnsureSuccessStatusCode();

        // 使用IAsyncEnumerable实现流式读取
        await using var stream = await response.Content.ReadAsStreamAsync();
        using var reader = new StreamReader(stream);
        
        StringBuilder result = new();
        while (!reader.EndOfStream)
        {
            var line = await reader.ReadLineAsync();
            if (!string.IsNullOrEmpty(line))
            {
                var data = JsonSerializer.Deserialize<JsonElement>(line);
                if (data.TryGetProperty("choices", out var choices))
                {
                    var content = choices[0].GetProperty("delta").GetProperty("content").GetString();
                    result.Append(content);
                    yield return content; // 实现逐字返回
                }
            }
        }
    }
}

4. 前端交互实现

Index.cshtml 对话界面：

html

<div class="chat-container">
    <div id="chatHistory" class="messages">
        <!-- 历史消息 -->
    </div>
    <div class="input-area">
        <input type="text" id="txtQuestion" placeholder="输入您的问题..." />
        <button οnclick="askQuestion()">发送</button>
    </div>
</div>

<script>
function askQuestion() {
    const question = document.getElementById('txtQuestion').value;
    const chatHistory = document.getElementById('chatHistory');
    
    // 添加用户消息
    chatHistory.innerHTML += `
        <div class="message user-message">
            <div class="avatar">👤</div>
            <div class="content">${question}</div>
        </div>`;
    
    // 建立SSE连接
    const eventSource = new EventSource(`/api/chat?question=${encodeURIComponent(question)}`);
    let answerDiv = document.createElement('div');
    
    eventSource.onmessage = (e) => {
        answerDiv.textContent += e.data;
        window.scrollTo(0, document.body.scrollHeight);
    };

    eventSource.onerror = () => {
        eventSource.close();
        answerDiv.textContent += "\n[对话结束]";
    };
}
</script>

运行 HTML

5. 流式响应API接口

ChatController.cs：

csharp

[ApiController]
[Route("api/[controller]")]
public class ChatController : Controller
{
    private readonly DeepSeekService _service;

    public ChatController(DeepSeekService service)
    {
        _service = service;
    }

    [HttpGet]
    public async Task ChatStream(string question)
    {
        Response.ContentType = "text/event-stream";
        
        await foreach (var chunk in _service.GetAnswerAsync(question))
        {
            await Response.WriteAsync($"data: {chunk}\n\n");
            await Response.Body.FlushAsync();
            await Task.Delay(50); // 模拟逐字输出效果
        }
        
        Response.Close();
    }
}