WPF快速创建DeepSeek本地自己的客户端-基础思路版本

开发工具：VS 2015
开发环境：.Net 4.0
使用技术：WPF

本篇文章内容：
本地部署DeepSeek以后一般使用网页工具（如Chatbox）或者DOS窗口与其对话。本篇文章使用WPF创建一个基础版的对话工具。

一、搭建本地DeepSeek环境

我参考的是一下几个教程：
1、DeepSeek本地搭建部署+搭建知识库+智能体详细图文教程
2、【问题记录】DeepSeek本地部署遇到问题
3、公司数据不泄露，DeepSeek R1本地化部署+web端访问+个人知识库搭建与使用，喂饭级实操教程，老旧笔记本竟跑出企业级AI
4、【大语言模型】本地快速部署Ollama运行大语言模型详细流程

二、vs2015 创建WPF项目

三、相关代码如下

Windows窗口界面

<Window x:Class="DeepSeekAI2.MainWindow"
        xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"
        xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"
        xmlns:d="http://schemas.microsoft.com/expression/blend/2008"
        xmlns:mc="http://schemas.openxmlformats.org/markup-compatibility/2006"
        xmlns:local="clr-namespace:DeepSeekAI2"
        mc:Ignorable="d"
        Title="MainWindow" Height="680" Width="800">
    <Grid Margin="10,0,15,5">
        <Grid.RowDefinitions>
            <RowDefinition Height="8.5*"/>
            <RowDefinition Height="1.5*"/>
        </Grid.RowDefinitions>
        <Grid.ColumnDefinitions>
            <ColumnDefinition Width="750"/>
        </Grid.ColumnDefinitions>

        <!--第一个格子，AI对话格子-->
        <Grid Grid.Row="0" Grid.Column="0">
            <ListBox Name="ChatListBox" HorizontalAlignment="Stretch" VerticalAlignment="Stretch">
                <ListBox.ItemTemplate>
                    <DataTemplate>
                        <TextBlock Text="{Binding}" TextWrapping="Wrap" MaxWidth="730"/>
                    </DataTemplate>
                </ListBox.ItemTemplate>
            </ListBox>
        </Grid>
        <!--第二个格子，用户输入框-->
        <Grid Grid.Row="1" Grid.Column="0">
            <Grid.ColumnDefinitions>
                <ColumnDefinition Width="8*" />
                <ColumnDefinition Width="2*"/>
            </Grid.ColumnDefinitions>
            <!--输入信息框-->
            <Grid Grid.Column="0">
                <TextBox Name="InputTextBox" HorizontalAlignment="Left" VerticalAlignment="Bottom" KeyDown="InputTextBox_KeyDown"
            Height="62" Width="522" Margin="61,0,0,14" />
            </Grid>
            <!--发送信息按钮框-->
            <Grid Grid.Column="1">
                <Button Name="SendButton" 
                    Content="Send" 
                    HorizontalAlignment="Right" 
                    VerticalAlignment="Bottom" 
                    Margin="0,0,58,20" 
                    Width="90" 
                    Height="50" 
                    Click="SendButton_Click" FontFamily="Arial Black" FontSize="13" Foreground="#FF424234"/>
            </Grid>
            <Grid Grid.Column="1">
                <Button Name="SendButton1" 
                    Content="new" 
                    HorizontalAlignment="Right" 
                    VerticalAlignment="Bottom" 
                    Margin="0,0,2,60" 
                    Width="30" 
                    Height="30" 
                    Click="SendButton_Click1" FontFamily="Cambria" Foreground="#FF424234" Background="#FFB6F5C2"/>
            </Grid>
        </Grid>
    </Grid>
</Window>

后端代码

using System;
using System.IO;
using System.Net.Http;
using System.Text;
using System.Threading;
using System.Threading.Tasks;
using System.Text.RegularExpressions;
using System.Windows;
using System.Windows.Input;
using System.Net;

namespace DeepSeekAI2
{
    /// <summary>
    /// MainWindow.xaml 的交互逻辑
    /// </summary>
    public partial class MainWindow : Window
    {
        public MainWindow()
        {
            InitializeComponent();
        }

        /// <summary>
        /// 输入按钮框
        /// </summary>
        /// <param name="sender"></param>
        /// <param name="e"></param>
        private void InputTextBox_KeyDown(object sender, KeyEventArgs e)
        {
            if (e.Key == Key.Enter)
            {
                RunAI();
                //InputTextBox.Text = "";
            }
        }

        /// <summary>
        /// 确认发送按钮
        /// </summary>
        /// <param name="sender"></param>
        /// <param name="e"></param>
        private void SendButton_Click(object sender, RoutedEventArgs e)
        {
            // 异步方法需在同步上下文中调用（需手动处理）
            RunAI();
            //InputTextBox.Text = "";
        }
        // 用于存储对话的历史记录
        static StringBuilder conversationHistory = new StringBuilder();
        static string apiUrl = "http://localhost:11434/api/generate";
            
        public void RunAI()
        {
            // 用户输入
            string userInput = InputTextBox.Text;
            // 如果输入不正确，不输出
            if (userInput.ToLower() == "" || userInput.ToLower() == "\n")
            {
                return;
            }
            // 用户输入添加到历史对话记录
            conversationHistory.AppendLine($"用户: {userInput}");
            ChatListBox.Items.Add("-----------用户：-----------");
            ChatListBox.Items.Add(userInput);
            var requestData = new
            {
                model = "deepseek-r1:1.5b",
                prompt = conversationHistory.ToString(),
                stream = true
            };

            string jsonContent = Newtonsoft.Json.JsonConvert.SerializeObject(requestData);
            byte[] byteArray = Encoding.UTF8.GetBytes(jsonContent);

            HttpWebRequest request = (HttpWebRequest)WebRequest.Create(apiUrl);
            request.Method = "POST";
            request.ContentType = "application/json";
            request.ContentLength = byteArray.Length;

            using (Stream dataStream = request.GetRequestStream())
            {
                dataStream.Write(byteArray, 0, byteArray.Length);
            }

            try
            {
                using (HttpWebResponse response = (HttpWebResponse)request.GetResponse())
                using (Stream responseStream = response.GetResponseStream())
                using (StreamReader reader = new StreamReader(responseStream))
                {
                    string line;

                    string line2 = "";
                    while ((line = reader.ReadLine()) != null)
                    {
                        if (!string.IsNullOrEmpty(line))
                        {
                            dynamic result = Newtonsoft.Json.JsonConvert.DeserializeObject(line);
                            if (result != null && result.response != null)
                            {
                                //Console.Write(result.response);
                                //Console.Out.Flush(); // 强制刷新控制台输出
                                //ChatListBox.Items.Add(result.response);
                                line2 += result.response;
                            }
                        }
                    }

                    // 处理AI回话
                    // 去掉所有的换行符
                    line2 = line2.Replace("\n\n", "");
                    // 使用正则表达式去掉 <think> 和 </think> 标签
                    line2 = Regex.Replace(line2, @"<\/?think>", "\n");
                    // 去掉开头的换行符
                    line2 = line2.TrimStart('\r', '\n');
                    ChatListBox.Items.Add("-----------DeepSeek: -----------");
                    //Console.WriteLine();  AI回话DeePSeek回话 line2
                    ChatListBox.Items.Add(line2);
                    conversationHistory.AppendLine($"DeepSeek: {line2}");
                    line2 = "";
                }
                InputTextBox.Text = "";
            }
            catch (WebException ex)
            {
                MessageBox.Show("请求异常: " + ex.Message);
                InputTextBox.Text = "";
            }
        }


        /// <summary>
        /// 开启新的对话
        /// </summary>
        /// <param name="sender"></param>
        /// <param name="e"></param>
        private void SendButton_Click1(object sender, RoutedEventArgs e)
        {
            //1 清空历史记录
            conversationHistory.Clear();
            //2 清空 ListBox 的内容
            ChatListBox.Items.Clear();
            //3 清空输入框
            InputTextBox.Text = "";
        }

    }
}

四、内容介绍

static string apiUrl = "http://localhost:11434/api/generate";

其中这个代码是本地DeepSeek默认的调用接口，如果自己修改了相关内容将此修改就可以

model = "deepseek-r1:1.5b"

这串代码的意思是指定使用本地安装的某个DeepSeek版本。

因为7b的版本在我电脑上太慢。所以直接使用最快的模型。

五、完成效果如下

这样就搭建了基础的对话模型。大家可以不断优化，做一个自己的对话模型。