Datawhale coze-ai-assistant：Task 5 发布

def generate_prompt(user_input, persona="AI Assistant"): prompt_template = f""" You are {persona}. Your task is to provide accurate and concise answers based on the following user query: User ...

### 实现AI聊天应用中的异步处理 在现代软件开发中，异步编程是一种重要的技术手段，尤其适用于高并发场景下的网络请求和服务交互。以下是关于如何在AI聊天应用中实现异步处理的具体方法。 #### C#与OpenAI API的异步集成 当使用C#语言与OpenAI API进行集成时，可以通过`HttpClient`类的异步方法来发起API请求。这种方法允许程序在等待响应的同时继续执行其他操作，从而提高性能和用户体验[^1]。下面是一个简单的代码示例： ```csharp using System; using System.Net.Http; using System.Text.Json; using System.Threading.Tasks; public class OpenAIApiClient { private readonly HttpClient _httpClient; public OpenAIApiClient(HttpClient httpClient) { _httpClient = httpClient ?? throw new ArgumentNullException(nameof(httpClient)); } public async Task<string> GetChatResponseAsync(string prompt) { var requestUri = "https://api.openai.com/v1/completions"; var requestBody = JsonSerializer.Serialize(new { model = "text-davinci-003", prompt, max_tokens = 50 }); var content = new StringContent(requestBody, Encoding.UTF8, "application/json"); using (var response = await _httpClient.PostAsync(requestUri, content)) { if (!response.IsSuccessStatusCode) throw new Exception($"Error calling OpenAI API: {await response.Content.ReadAsStringAsync()}"); var responseBody = await response.Content.ReadFromJsonAsync<OpenAIResponse>(); return responseBody?.Choices?[0]?.Text; } } } public class OpenAIResponse { public Choice[] Choices { get; set; } } public class Choice { public string Text { get; set; } } ``` 上述代码展示了如何利用`PostAsync`方法向OpenAI API发送异步请求，并通过`ReadFromJsonAsync`解析返回的数据。 --- #### Unity 中基于OpenAI的异步聊天机器人 在Unity环境下，可以借助协程（Coroutine）或者.NET标准库中的Task机制来实现异步通信。以下是一段基于Task的代码片段，用于演示如何从Unity脚本中调用OpenAI服务[^2]: ```csharp using UnityEngine; using System.Collections; using System.Net.Http; using System.Text.Json; using System.Threading.Tasks; public class ChatBotController : MonoBehaviour { private static readonly HttpClient client = new HttpClient(); void Start() { StartCoroutine(SendMessageToChatGPT("你好")); } IEnumerator SendMessageToChatGPT(string message) { yield return new WaitUntil(() => !string.IsNullOrEmpty(message)); var task = SendRequestAsync(message); while (!task.IsCompleted) yield return null; Debug.Log(task.Result); } private async Task<string> SendRequestAsync(string input) { var url = "https://api.openai.com/v1/chat/completions"; var body = JsonSerializer.Serialize(new { model = "gpt-3.5-turbo", messages = new[] { new { role = "user", content = input }, new { role = "assistant", content = "" } } }); var httpContent = new StringContent(body, Encoding.UTF8, "application/json"); var httpResponse = await client.PostAsync(url, httpContent); if (httpResponse.IsSuccessStatusCode) { var jsonResponse = await httpResponse.Content.ReadFromJsonAsync<dynamic>(); return jsonResponse.choices[0].message.content.ToString(); } return $"Error: {(int)httpResponse.StatusCode} - {httpResponse.ReasonPhrase}"; } } ``` 此代码定义了一个名为`SendMessageToChatGPT`的方法，该方法会启动一个协程，在后台完成HTTP POST请求并接收来自OpenAI的服务答复。 --- #### ZHIPU AI 的异步函数调用 如果选择的是ZHIPU AI作为后端支持，则可以直接采用其官方文档推荐的方式编写异步逻辑。例如，初始化`ChatZhipuAI`对象之后，可通过`agenerate`方法生成对话内容[^4]： ```python import asyncio from zhipuai import ChatZhipuAI async def main(): chat_instance = ChatZhipuAI(model="glm-4", temperature=0.7) messages = [ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "What is the capital of France?"}, {"role": "assistant", "content": ""} ] response = await chat_instance.agenerate(messages) print(f"Assistant's reply: {response}") if __name__ == "__main__": asyncio.run(main()) ``` 这段Python代码清晰地展现了如何运用异步I/O操作简化多线程管理流程，同时保持良好的可读性。 --- #### Coze API 的异步接口访问 针对Coze API的应用开发同样提供了完善的异步功能支持。开发者只需按照官方指南配置好环境变量以及必要的依赖项即可开始工作[^5]。这里给出一段伪代码供参考： ```javascript const cozeApi = require('coze-api'); (async function() { const apiInstance = new cozeApi.ChatService({ apiKey: 'your_api_key_here', baseUrl: 'https://api.coze.ai' }); try { let result = await apiInstance.sendMessage({ text: 'Tell me about artificial intelligence.' }); console.log(result.message); // 输出机器人的回应 } catch (error) { console.error(`Failed to send message due to ${error}`); } })(); ``` 以上JavaScript代码片段体现了如何安全高效地调用远程RESTful Web Service以获得即时反馈。 ---