使用PocketFlowSharp创建一个Human_Evaluation示例

效果

实践

有时候AI生成的结果我们并不满意在进入下一步之前，我们需要对AI生成的结果进行人工审核，同意了才能进入下一个流程。

Human_Evaluation就是人工判断的一个简单示例。

 internal class Program { static async Task Main(string[] args) { // Load .env file DotEnv.Load(); // Get environment variables from .env file var envVars = DotEnv.Read(); string ModelName = envVars["ModelName"]; string EndPoint = envVars["EndPoint"]; string ApiKey = envVars["ApiKey"]; Utils.ModelName = ModelName; Utils.EndPoint = EndPoint; Utils.ApiKey = ApiKey; // 创建共享数据字典 var shared = new Dictionary<string, object>(); // 创建并运行流程 var humanEvalFlow = CreateFlow(); Console.WriteLine("\n欢迎使用人工判断示例！"); Console.WriteLine("------------------------"); await humanEvalFlow.RunAsync(shared); Console.WriteLine("\n感谢使用人工判断示例！"); } static AsyncFlow CreateFlow() { // 创建节点实例 var inputNode = new TaskInputNode(); var aiResponseNode = new AIResponseNode(); var humanApprovalNode = new HumanApprovalNode(); var endNode = new NoOpNode(); // 创建从输入节点开始的流程 var flow = new AsyncFlow(inputNode); // 连接节点 _ = inputNode -"generate" - aiResponseNode; _ = aiResponseNode -"approve" - humanApprovalNode; _ = humanApprovalNode -"retry" - aiResponseNode; // 不接受时重新生成 _ = humanApprovalNode -"accept" - endNode; // 接受时结束流程 return flow; } }

看一下整体的流程图：

输入节点：

 public class TaskInputNode : AsyncNode { protected override async Task<object> PrepAsync(Dictionary<string, object> shared) { Console.WriteLine("\n请输入需要AI处理的任务："); string task = Console.ReadLine(); return task; } protected override async Task<object> ExecAsync(object prepResult) { string task = (string)prepResult; Console.WriteLine($"\n已收到任务：{task}"); return task; } protected override async Task<object> PostAsync(Dictionary<string, object> shared, object prepResult, object execResult) { string task = (string)execResult; shared["task"] = task; return"generate"; } }

AI回复节点：

public class AIResponseNode : AsyncNode{ private static int attemptCount = 0; protected override async Task<object> PrepAsync(Dictionary<string, object> shared) { return shared["task"]; } protected override async Task<object> ExecAsync(object prepResult) { string task = (string)prepResult; attemptCount++; Console.WriteLine("AI正在生成回复...\n"); Console.WriteLine($"任务：{task}\n"); Console.WriteLine($"这是第 {attemptCount} 次生成的AI回复：\n"); var result = await Utils.CallLLMStreamingAsync(task); string response=""; Console.ForegroundColor = ConsoleColor.Green; await foreach (StreamingChatCompletionUpdate completionUpdate in result) { if (completionUpdate.ContentUpdate.Count > 0) { Console.Write(completionUpdate.ContentUpdate[0].Text); response += completionUpdate.ContentUpdate[0].Text.ToString(); } } Console.ForegroundColor = ConsoleColor.White; return response; } protected override async Task<object> PostAsync(Dictionary<string, object> shared, object prepResult, object execResult) { string response = (string)execResult; shared["response"] = response; return"approve"; }}

人工审核节点：

 public class HumanApprovalNode : AsyncNode { protected override async Task<object> PrepAsync(Dictionary<string, object> shared) { return shared["response"]; } protected override async Task<object> ExecAsync(object prepResult) { Console.Write("\n您接受这个AI回复吗？(y/n):"); string answer = Console.ReadLine()?.ToLower() ??"n"; return answer; } protected override async Task<object> PostAsync(Dictionary<string, object> shared, object prepResult, object execResult) { string answer = (string)execResult; if (answer =="y") { Console.WriteLine($"已接受的回复：\n{shared["response"]}"); return"accept"; } else { Console.WriteLine("\n好的，让AI重新生成回复..."); return"retry"; } } }

结束节点：

 public class NoOpNode : AsyncNode { protected override async Task<object> PrepAsync(Dictionary<string, object> shared) => null; protected override async Task<object> ExecAsync(object prepResult) => null; protected override async Task<object> PostAsync(Dictionary<string, object> shared, object prepResult, object execResult) => null; }

帮助类：

 public static class Utils { public static string ModelName { get; set; } public static string EndPoint { get; set; } public static string ApiKey { get; set; } public static async Task<string> CallLLMAsync(string prompt) { ApiKeyCredential apiKeyCredential = new ApiKeyCredential(ApiKey); OpenAIClientOptions openAIClientOptions = new OpenAIClientOptions(); openAIClientOptions.Endpoint = new Uri(EndPoint); ChatClient client = new(model: ModelName, apiKeyCredential, openAIClientOptions); ChatCompletion completion = await client.CompleteChatAsync(prompt); return completion.Content[0].Text; } public static async Task<AsyncCollectionResult<StreamingChatCompletionUpdate>> CallLLMStreamingAsync(string prompt) { ApiKeyCredential apiKeyCredential = new ApiKeyCredential(ApiKey); OpenAIClientOptions openAIClientOptions = new OpenAIClientOptions(); openAIClientOptions.Endpoint = new Uri(EndPoint); ChatClient client = new(model: ModelName, apiKeyCredential, openAIClientOptions); var completion = client.CompleteChatStreamingAsync(prompt); return completion; } }

全部代码在：https://github.com/Ming-jiayou/PocketFlowSharp/tree/main/PocketFlowSharpSamples.Console/Human_Evaluation