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c#通过网上AI大模型实现对话功能

目录

    • 基础使用
    • 给大模型额外提供函数能力
      • 用Microsoft.Extensions.AI库实现
      • 用json格式回答

基础使用

https://siliconflow.cn/网站有些免费的大模型可以使用,去注册个账户,拿到apikey
引用 nuget

Microsoft.Extensions.AI.OpenAI

using Microsoft.Extensions.AI;
using OpenAI;
using System.ClientModel;namespace ConsoleApp2
{internal class Program{static async Task Main(string[] args){OpenAIClientOptions openAIClientOptions = new OpenAIClientOptions();openAIClientOptions.Endpoint = new Uri("https://api.siliconflow.cn/v1");// SiliconCloud API Keystring mySiliconCloudAPIKey = "你的api key";OpenAIClient client = new OpenAIClient(new ApiKeyCredential(mySiliconCloudAPIKey), openAIClientOptions);IChatClient chatClient = client.AsChatClient("Qwen/Qwen2.5-7B-Instruct");while (true){var response = chatClient.CompleteStreamingAsync(Console.ReadLine());//手动输入问题await foreach (var item in response){Console.Write(item.Text);}Console.Write("\r\n\r\n");}}}
}

给大模型额外提供函数能力


using OpenAI;
using OpenAI.Chat;
using System.ClientModel;namespace ConsoleApp2
{internal class Program{static async Task Main(string[] args){OpenAIClientOptions openAIClientOptions = new OpenAIClientOptions();openAIClientOptions.Endpoint = new Uri("https://api.siliconflow.cn/v1");// SiliconCloud API Keystring mySiliconCloudAPIKey = "你的api key";OpenAIClient client = new OpenAIClient(new ApiKeyCredential(mySiliconCloudAPIKey), openAIClientOptions);var assistantClient = client.GetChatClient("Qwen/Qwen2.5-7B-Instruct");await FunctionCallPlayground(assistantClient, "how is the weather today in beijing?");Console.ReadKey();}private static async Task FunctionCallPlayground(ChatClient chatClient, string prompt){Console.WriteLine(prompt);var messages = new[]{new UserChatMessage(  prompt)};BinaryData functionParameters = BinaryData.FromBytes("""{"type": "object","properties": {"city": {"type": "string","description": "The name of the city to query weather for."}},"required": ["city"],"additionalProperties": false}"""u8.ToArray());var chatTool = ChatTool.CreateFunctionTool("get_weather", "Get the current weather for a given city.", functionParameters);var options = new ChatCompletionOptions{Temperature = 0.01f,TopP = 0.95f,};options.Tools.Add(chatTool);var response = chatClient.CompleteChat(messages, options);// 假设我们只处理第一个工具调用请求var func1Name = response.Value.ToolCalls[0].FunctionName;var func1Args = System.Text.Json.JsonSerializer.Deserialize<Dictionary<string,string>>( response.Value.ToolCalls[0].FunctionArguments.ToString());var func1Out = await GetWeather(func1Args["city"] );options = new ChatCompletionOptions{Temperature = 0.01f,TopP = 0.95f,};response = chatClient.CompleteChat(new ChatMessage[] { messages[0] , new ToolChatMessage(response.Value.ToolCalls[0].Id, func1Out) }, options);Console.WriteLine(response.Value.Content.FirstOrDefault()?.Text);}private static async Task<string> GetWeather(string city){return $"23摄氏度";}}}

用Microsoft.Extensions.AI库实现


using Microsoft.Extensions.AI;
using OpenAI;
using OpenAI.Chat;
using System.ClientModel;namespace ConsoleApp2
{internal class Program{const string APIKEY = "你的apikey";static async Task Main(string[] args){OpenAIClientOptions openAIClientOptions = new OpenAIClientOptions();openAIClientOptions.Endpoint = new Uri("https://api.siliconflow.cn/v1");// SiliconCloud API Keystring mySiliconCloudAPIKey = APIKEY;var weathfunc = new GetWeatherFunction();var humidtyfunc = new GetHumidityFunction();ChatOptions chatOptions = new ChatOptions(){Temperature = 0.01f,TopP = 0.95f,Tools = new AIFunction[] { weathfunc, humidtyfunc }};OpenAIClient client = new OpenAIClient(new ApiKeyCredential(mySiliconCloudAPIKey), openAIClientOptions);IChatClient chatClient = client.AsChatClient("Qwen/Qwen2.5-7B-Instruct");while (true){var question = Console.ReadLine();//手动输入问题var response = await chatClient.CompleteAsync(question, chatOptions);_check:if(response.FinishReason == Microsoft.Extensions.AI.ChatFinishReason.ToolCalls){List<AIContent> callRets = new List<AIContent>();foreach( var aiContent in response.Choices[0].Contents){if(aiContent is FunctionCallContent callContent){var callid = callContent.CallId;var func = (AIFunction)chatOptions.Tools.FirstOrDefault(m=>((AIFunction)m).Metadata.Name == callContent.Name);var ret  =await func!.InvokeAsync(callContent.Arguments);callRets.Add(new FunctionResultContent(callid , callContent.Name , ret));}}List<Microsoft.Extensions.AI.ChatMessage> list = new List<Microsoft.Extensions.AI.ChatMessage>();list.Add(new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.User, question));list.Add(new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.Tool, callRets));response = await chatClient.CompleteAsync(list, chatOptions);goto _check;}else{Console.WriteLine(response.Choices[0].Contents.FirstOrDefault()?.ToString());}Console.Write("\r\n");}}}public class GetWeatherFunction : AIFunction{Microsoft.Extensions.AI.AIFunctionMetadata _Metadata;public override AIFunctionMetadata Metadata => _Metadata;public GetWeatherFunction() {_Metadata = new Microsoft.Extensions.AI.AIFunctionMetadata("get_weather"){Description = "Get the current weather for a given city.",Parameters = new[] { new AIFunctionParameterMetadata("city") { ParameterType = typeof(string),Description = "The name of the city to query weather for.",IsRequired = true,} },  };}protected override async Task<object?> InvokeCoreAsync(IEnumerable<KeyValuePair<string, object?>> arguments, CancellationToken cancellationToken){return $"23摄氏度";}}public class GetHumidityFunction : AIFunction{Microsoft.Extensions.AI.AIFunctionMetadata _Metadata;public override AIFunctionMetadata Metadata => _Metadata;public GetHumidityFunction(){_Metadata = new Microsoft.Extensions.AI.AIFunctionMetadata("get_humidity"){Description = "获取指定城市的湿度",Parameters = new[] { new AIFunctionParameterMetadata("city") {ParameterType = typeof(string),Description = "要获取湿度的城市名称",IsRequired = true,} },};}protected override async Task<object?> InvokeCoreAsync(IEnumerable<KeyValuePair<string, object?>> arguments, CancellationToken cancellationToken){return $"70%";}}}

用json格式回答

通过设置ResponseFormat 为json,可以让大模型以json格式输出

上面代码修改为:

                    List<Microsoft.Extensions.AI.ChatMessage> list = new List<Microsoft.Extensions.AI.ChatMessage>();list.Add(new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.User, question));list.Add(new Microsoft.Extensions.AI.ChatMessage(Microsoft.Extensions.AI.ChatRole.Tool, callRets));ChatOptions chatOptions2 = new ChatOptions(){Temperature = 0.01f,TopP = 0.95f,MaxOutputTokens = int.MaxValue,ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.Json,};response = await chatClient.CompleteAsync(list, chatOptions2);

注意:如果你的提问需要调用你自己定义的函数去计算,那么,提问时不要设置ResponseFormat ,否则回答类型不会是FinishReason == Microsoft.Extensions.AI.ChatFinishReason.ToolCalls,也就无法触发你的程序去调用函数了,只有计算完结果后,回传结果给大模型时才设置 ResponseFormat = Microsoft.Extensions.AI.ChatResponseFormat.Json

提问需要这么提问:
北京现在的温度和湿度是多少?请用这种格式回答:[“温度值”,“湿度值”]

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