qwen2.5

下载qwen2.5

https://modelscope.cn/models/Qwen/Qwen2.5-7B-Instruct-GGUF

安装ollama

https://www.ollama.com/

导入模型

新建Modelfile

FROM ./qwen2.5-7b-instruct-q5_k_m.gguf
# set the temperature to 0.7 [higher is more creative, lower is more coherent]
PARAMETER temperature 0.7
PARAMETER top_p 0.8
PARAMETER repeat_penalty 1.05
TEMPLATE """{{ if .Messages }}
{{- if or .System .Tools }}<|im_start|>system
{{ .System }}
{{- if .Tools }}
# Tools
You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. Here are the available tools:
<tools>{{- range .Tools }}{{ .Function }}{{- end }}</tools>
For each function call, return a JSON object with function name and arguments within <tool_call></tool_call> XML tags as follows:
<tool_call>
{"name": <function-name>, "arguments": <args-json-object>}
</tool_call>{{- end }}<|im_end|>{{- end }}
{{- range .Messages }}
{{- if eq .Role "user" }}
<|im_start|>{{ .Role }}
{{ .Content }}<|im_end|>
{{- else if eq .Role "assistant" }}
<|im_start|>{{ .Role }}
{{- if .Content }}
{{ .Content }}
{{- end }}
{{- if .ToolCalls }}
<tool_call>
{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
{{ end }}</tool_call>
{{- end }}<|im_end|>
{{- else if eq .Role "tool" }}
<|im_start|>user
<tool_response>
{{ .Content }}
</tool_response><|im_end|>
{{- end }}
{{- end }}
<|im_start|>assistant
{{ else }}{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ end }}
"""

导入

ollama create qwen2.5 --file ./ModelFile

qwq

如果使用ollama直接拉取则直接支持function call

测试

EmailTools.cs

using Microsoft.SemanticKernel;
using System.ComponentModel;

namespace stu
{
    public class EmailTools
    {
        /// <summary>
        /// 发送邮件
        /// </summary>
        /// <param name="email"></param>
        /// <param name="title"></param>
        /// <param name="content"></param>
        /// <returns></returns>
        [KernelFunction, Description("发送邮件")]
        public string SendEmail([Description("接收人")] string email, [Description("邮件主题")] string title,
                [Description("邮件内容")] string? content)
        {
            Console.ForegroundColor = ConsoleColor.Green;
            Console.WriteLine($"发送邮件给 {email} 主题：{title} 内容：{content}");
            Console.ForegroundColor = ConsoleColor.White;
            // 这里模拟发送邮件
            return "邮件发送成功";
        }
    }
}

OpenAIHttpClientHandler.cs

namespace stu
{
    /// <summary>
    /// OpenAI客户端
    /// </summary>
    public class OpenAIHttpClientHandler : HttpClientHandler
    {
        private readonly string _uri;

        public OpenAIHttpClientHandler(string uri) => _uri = uri.TrimEnd('/');

        /// <summary>
        /// 发送消息
        /// </summary>
        /// <param name="request"></param>
        /// <param name="cancellationToken"></param>
        /// <returns></returns>
        protected override async Task<HttpResponseMessage> SendAsync(HttpRequestMessage request,
            CancellationToken cancellationToken)
        {
            UriBuilder uriBuilder;
            if (request.RequestUri?.LocalPath == "/v1/chat/completions")
            {
                uriBuilder = new UriBuilder(_uri + "/v1/chat/completions");
                request.RequestUri = uriBuilder.Uri;
            }
            else if (request.RequestUri?.LocalPath == "/v1/embeddings")
            {
                uriBuilder = new UriBuilder(_uri + "/v1/embeddings");
                request.RequestUri = uriBuilder.Uri;
            }

            return await base.SendAsync(request, cancellationToken);
        }
    }
}

调用

using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.ChatCompletion;
using Microsoft.SemanticKernel.Connectors.OpenAI;
using System.Text;

namespace stu
{
    internal class Program
    {
        static async Task Main(string[] args)
        {
            var modelName = "qwen2.5";
            //modelName = "qwq";
            var kernel = Kernel.CreateBuilder()
               .AddOpenAIChatCompletion(
                   modelId: modelName,
                   apiKey: "sddssd",
                   httpClient: new HttpClient(new OpenAIHttpClientHandler("http://127.0.0.1:11434")))
               .Build();
            kernel.Plugins.AddFromType<EmailTools>();
            var emailPrompt =
@"
## 需求：
- 我需要解决用户发送邮件问题，邮件参数包含以下参数
    - 收件人邮箱
        - required
        - email 
    - 邮件主题
        - required
        - 长度限制 100
        - title
    - 邮件内容
        - content
        - required 
- 在上面的参数如果是required则是必须的，如果用户没有提供那么你需要提示用户缺少哪些参数。
- 如果用户提供了参数，您需要提示不合法的参数，你不要提供测试用例，你需要提示用户哪些参数不合法。
- 上面要求都满足以后，需要提问用户是否确认发送,如果用户确认发送，那么你需要调用发送邮件。
";
            var chatHistory = new ChatHistory();
            var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
            StringBuilder resultContent = new StringBuilder();
            while (true)
            {
                Console.Write("用户 > ");
                var input = Console.ReadLine();
                if (input == "/bye")
                {
                    Console.WriteLine("再见~~");
                    break;
                }
                chatHistory.AddUserMessage(input);

                // 流式输出
                var settings = new OpenAIPromptExecutionSettings()
                {
                    ChatSystemPrompt = emailPrompt,
                    MaxTokens = 50000,
                    Temperature = 0.5,
                    TopP = 1,
                    ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions
                };
                Console.Write($"\n助手 >");
                resultContent.Clear();
                await foreach (var message in chatCompletionService
                    .GetStreamingChatMessageContentsAsync(chatHistory,settings,kernel))
                {
                    Console.Write(message.Content);
                    resultContent.Append(message.Content);
                }
                Console.Write("\n");
                chatHistory.AddAssistantMessage(resultContent.ToString());
            }
            Console.ReadKey();
        }
    }
}