【C#实现手写Ollama服务交互，实现本地模型对话】

前言

C#手写Ollama服务交互，实现本地模型对话

最近使用C#调用OllamaSharpe库实现Ollama本地对话，然后思考着能否自己实现这个功能。经过一番查找，和查看OllamaSharpe源码发现确实可以。其实就是开启Ollama服务后，发送HTTP请求，获取返回结果以及一些数据处理。

基本流程

1、启动Ollama服务进程。
2、创建HttpClient对象。
3、创建请求体（参数:模型名称、提示语、是否流式生成）。
4、将请求体序列化为JSON。
5、创建HTTP请求内容。
6、发送POST请求，并确保请求成功。
7、读取并返回响应内容，并解析相应字符串。
8、返回结果。

 		//创建请求体:模型名称、提示语、是否流式生成var request = new RequestModel{Model = model,Prompt = prompt,Stream = false};// 将请求体序列化为JSONvar json = JsonSerializer.Serialize(request);// 创建HTTP请求内容var content = new StringContent(json, Encoding.UTF8, "application/json");// 发送POST请求var response = await _httpClient.PostAsync("/api/generate", content);// 确保请求成功response.EnsureSuccessStatusCode();// 读取并返回响应内容string responseString = await response.Content.ReadAsStringAsync();///解析相应字符串ResponseModel results = JsonSerializer.Deserialize<ResponseModel>(responseString);//返回结果return results.Response;

项目结构

OllamaClient ：实现基本的对话请求、获取模型列表功能。
Model ：创建模型结果的一些参数
RequestModel：请求参数模型
ResponseModel：结果参数模型，用于解析返回的结果。
MainWindow：用户界面
MainWindowViewModel：界面交互业务处理

案例

模型加载

发送聊天

代码

OllamaSharpe

Ollama客户端 OllamaClient

public class OllamaClient{public IEnumerable<Model> ModelList { get; set; }private readonly HttpClient _httpClient;public OllamaClient(string baseAddress = "http://localhost:11434"){_httpClient = new HttpClient{BaseAddress = new Uri(baseAddress)};ExecuteCommand("ollama list");  //启动Ollama服务}/// <summary>/// 异步生成文本/// </summary>public async Task<string> GenerateTextAsync(string model, string prompt){try{//创建请求体:模型名称、提示语、是否流式生成var request = new RequestModel{Model = model,Prompt = prompt,Stream = false};// 将请求体序列化为JSONvar json = JsonSerializer.Serialize(request);// 创建HTTP请求内容var content = new StringContent(json, Encoding.UTF8, "application/json");// 发送POST请求var response = await _httpClient.PostAsync("/api/generate", content);// 确保请求成功response.EnsureSuccessStatusCode();// 读取并返回响应内容string responseString = await response.Content.ReadAsStringAsync();///解析相应字符串ResponseModel results = JsonSerializer.Deserialize<ResponseModel>(responseString);//返回结果return results.Response;}catch (HttpRequestException e){throw new Exception($"Request failed: {e.Message}");}}/// <summary>/// 异步流式生成文本/// </summary>public async IAsyncEnumerable<string> StreamGenerateTextAsync(string model, string prompt){//创建请求体:模型名称、提示语、是否流式生成var request = new RequestModel{Model = model,Prompt = prompt, Stream = true};// 将请求体序列化为JSONvar json = JsonSerializer.Serialize(request);//创建HTTP请求内容var content = new StringContent(json, Encoding.UTF8, "application/json");//发送POST请求using var response = await _httpClient.PostAsync("/api/generate", content);// 确保请求成功response.EnsureSuccessStatusCode();// 读取流并解析为ResponseModelusing var stream = await response.Content.ReadAsStreamAsync();// 创建流读取器using var reader = new StreamReader(stream);// 循环读取流while (!reader.EndOfStream){// 读取一行var line = await reader.ReadLineAsync();// 如果行不为空，则解析为ResponseModel并返回if (!string.IsNullOrEmpty(line)){var partial = JsonSerializer.Deserialize<ResponseModel>(line);yield return partial.Response;}}}/// <summary>/// 异步获取本地模型列表/// </summary>public async Task<IEnumerable<Model>> ListLocalModelsAsync(){//相应请求HttpResponseMessage responseMessage = await _httpClient.GetAsync("/api/tags").ConfigureAwait(false);;//确保请求成功responseMessage.EnsureSuccessStatusCode();//读取响应string response = await responseMessage.Content.ReadAsStringAsync();//读取流并解析为LocalModelsLocalModels localModel = JsonSerializer.Deserialize<LocalModels>(response);await Task.Delay(3000);//返回结果ModelList = localModel.Models;return localModel.Models;}// <summary>/// 执行CMD指令：用于启动Ollama服务，/// </summary>public static bool ExecuteCommand(string command){// 创建一个新的进程启动信息ProcessStartInfo processStartInfo = new ProcessStartInfo{FileName = "cmd.exe",           // 设置要启动的程序为cmd.exeArguments = $"/C {command}",    // 设置要执行的命令UseShellExecute = true,         // 使用操作系统shell启动进程CreateNoWindow = false,         //不创建窗体};try{Process process = Process.Start(processStartInfo);// 启动进程process.WaitForExit();    // 等待进程退出process.Close();          // 返回是否成功执行return process.ExitCode == 0;}catch (Exception ex){Debug.WriteLine($"发生错误: {ex.Message}");// 其他异常处理return false;}}}

请求模型：RequestModel

/// <summary>
/// 请求模型
/// </summary>
public class RequestModel
{public string Model { get; set; }public string Prompt { get; set; }public bool Stream { get; set; }
}

响应模型：ResponseModel

/// <summary>
/// 响应模型
/// </summary>
public class ResponseModel
{/// <summary>/// 模型名称/// </summary>[JsonPropertyName("model")]public string Model { get; set; }/// <summary>/// 创建时间/// </summary>[JsonPropertyName("created_at")]public string CreatedTime { get; set; }/// <summary>/// 响应：返回文本/// </summary>[JsonPropertyName("response")]public string Response { get; set; }/// <summary>/// 是否结束/// </summary>[JsonPropertyName("done")]public bool Done { get; set; }/// <summary>/// 结束原因/// </summary>[JsonPropertyName("done_reason")]public string Done_Reason { get; set; }/// <summary>/// 上下文/// </summary>[JsonPropertyName("context")]public List<int> Context { get; set; }/// <summary>/// 总耗时/// </summary>[JsonPropertyName("total_duration")]public long TotalDuration { get; set; }/// <summary>/// 加载耗时/// </summary>[JsonPropertyName("load_duration")]public long LoadDuration { get; set; }/// <summary>/// 提示词评估次数/// </summary>[JsonPropertyName("prompt_eval_count")]public long PromptEvalCount { get; set; }/// <summary>/// 提示词评估耗时/// </summary>[JsonPropertyName("prompt_eval_duration")]public long PromptEvalDuration { get; set; }/// <summary>/// 评估次数/// </summary>[JsonPropertyName("eval_count")]public long EvalCount { get; set; }/// <summary>/// 评估耗时/// </summary>[JsonPropertyName("eval_duration")]public long EvalDuration { get; set; }
}

结果模型：LocalModels | Model

/// <summary>
/// 本地模型
/// </summary>
public class LocalModels
{[JsonPropertyName("models")]public IEnumerable<Model> Models { get; set; }
}
/// <summary>
/// 模型
/// </summary>
public class Model
{/// <summary>/// 模型名称/// </summary>[JsonPropertyName("name")]public string Name { get; set; }/// <summary>/// 模型名称/// </summary>[JsonPropertyName("model")]public string ModelName { get; set; }/// <summary>/// 修改时间/// </summary>[JsonPropertyName("modified_at")]public DateTime ModifiedAt { get; set; }/// <summary>/// 大小/// </summary>[JsonPropertyName("size")]public long Size { get; set; }/// <summary>/// /// </summary>[JsonPropertyName("digest")]public string Digest { get; set; }/// <summary>/// 模型细节/// </summary>[JsonPropertyName("details")]public ModelDetails Details { get; set; }
}/// <summary>
/// 模型细节
/// </summary>
public class ModelDetails
{/// <summary>/// 父模型/// </summary>[JsonPropertyName("parent_model")]public string ParentModel { get; set; }/// <summary>/// 格式/// </summary>[JsonPropertyName("format")]public string Format { get; set; }/// <summary>/// /// </summary>[JsonPropertyName("family")]public string Family { get; set; }/// <summary>/// /// </summary>[JsonPropertyName("families")]public List<string> Families { get; set; }/// <summary>/// 参数大小/// </summary>[JsonPropertyName("parameter_size")]public string ParameterSize { get; set; }/// <summary>/// 质量等级/// </summary>[JsonPropertyName("quantization_level")]public string QuantizationLevel { get; set; }
}

简单的界面

MainWindow

<Window.DataContext><local:MainWindowViewModel x:Name="ViewModel"/>
</Window.DataContext>
<Grid><Grid.RowDefinitions><RowDefinition Height="50"/><RowDefinition Height="*"/><RowDefinition Height="300"/></Grid.RowDefinitions><Grid Grid.Row="0"><WrapPanel VerticalAlignment="Center" Margin="5"><Label Content="模型列表" Margin="5"/><ComboBox Width="200" Margin="5" Name="ModelListBox"ItemsSource="{Binding ModelCollection}"SelectedItem="{Binding SelectedModel}"/></WrapPanel></Grid><Grid Grid.Row="1"><TextBox x:Name="OutputBox" Text="{Binding OutputText}"ScrollViewer.HorizontalScrollBarVisibility="Visible"ScrollViewer.VerticalScrollBarVisibility="Visible"/></Grid><Grid Grid.Row="2"><Grid.RowDefinitions><RowDefinition Height="*"/><RowDefinition Height="50"/></Grid.RowDefinitions><TextBox Grid.Row="0" x:Name="InputBox" Background="#AAAAAA"Text="{Binding InputText}"TextWrapping="WrapWithOverflow"ScrollViewer.VerticalScrollBarVisibility="Auto"ScrollViewer.HorizontalScrollBarVisibility="Auto" ></TextBox><WrapPanel Grid.Row="1" HorizontalAlignment="Right" VerticalAlignment="Center" Margin="5"><Button  Grid.Row="1"  Width="100" Height="30" x:Name="Btn_Submit" Command="{Binding SendQuestionCommand}">发送</Button></WrapPanel></Grid>
</Grid>

MainWindowViewModel

public class MainWindowViewModel: PropertyChangedBase
{#region 字段、属性private string _inputText = "";         //输入文本private string _outputText = "";        //输出文本private OllamaClient _ollama;            //Ollama客户端private string _selectedModel = "deepseek-r1:1.5b";     //选择模型private ObservableCollection<string> _modelCollection;  //模型列表#region 属性public ObservableCollection<string> ModelCollection{get => _modelCollection;set{if (_modelCollection != value){_modelCollection = value;OnPropertyChanged();}}}public string SelectedModel{get => _selectedModel;set{if (_selectedModel != value){_selectedModel = value;OnPropertyChanged();}}}private OllamaClient Ollama { get => _ollama; }public string OutputText{get => _outputText;set{if (_outputText != value){_outputText = value;OnPropertyChanged();}}}public string InputText{get => _inputText;set{if (_inputText != value){_inputText = value;OnPropertyChanged();}}}public ICommand SendQuestionCommand { get; set; }#endregion#endregionpublic MainWindowViewModel(){Initialze();}/// <summary>/// 初始化/// </summary>private void Initialze(){_ollama = new OllamaClient();_modelCollection = new ObservableCollection<string>();SelectedModel = "deepseek-r1:1.5b";var models = Ollama.ListLocalModelsAsync();AppendLine($"模型列表;{Environment.NewLine}");foreach (var model in models.Result){ModelCollection.Add(model.ModelName);AppendLine($"{model.ModelName}，{FormatFileSize(model.Size)}\r\n");}SendQuestionCommand = new ParameterlessCommand(OnSendQuestion);}/// <summary>/// 格式化文件大小/// </summary>private string FormatFileSize(long bytes){string[] sizes = { "B", "KB", "MB", "GB", "TB" };int order = 0;while (bytes >= 1024 && order < sizes.Length - 1){order++;bytes = bytes / 1024;}return $"{bytes:0.##} {sizes[order]}";}/// <summary>/// 发送文本/// </summary>public async void OnSendQuestion(){try{AppendLine($"【用户】{InputText}\r\n\r\n");AppendLine($"【AI】\r\n\r\n");await foreach (var answerToken in Ollama.StreamGenerateTextAsync(SelectedModel, InputText)){AppendText(answerToken);}AppendLine($"\r\n");}catch (Exception ex){AppendText($"Error: {ex.Message}");}}/// <summary>/// 附加文本/// </summary>private async void AppendText(string text){Debug.Print($"{text}");OutputText += text;}/// <summary>/// 附加文本行/// </summary>private async void AppendLine(string text){Debug.Print($"{text}");OutputText += $"{text}\r\n";}
}

 /// <summary>/// 属性变更/// </summary>public class PropertyChangedBase : INotifyPropertyChanged{public event PropertyChangedEventHandler PropertyChanged;protected void OnPropertyChanged([CallerMemberName] string propertyName = null){PropertyChanged?.Invoke(this, new PropertyChangedEventArgs(propertyName));}}

总结

案例代码实现了与Ollama的HTTP交互，通过使用HttpClient、JSON序列化和错误处理，提供了一个简洁的异步文本生成接口。适合直接调用本地Ollama服务的场景，更多功能，可以后续拓展。