示例代码框架,展示了如何用C#结合AI服务(如OpenAI API)实现PR处理、单元测试生成和Bug修复的自动化流程。需要已配置好AI服务访问权限:
基础AI服务封装
csharp
using System.Net.Http;
using System.Text;
using Newtonsoft.Json;
public class AIServiceClient
{
private readonly string _apiKey;
private readonly HttpClient _httpClient = new();
public AIServiceClient(string apiKey) => _apiKey = apiKey;
public async Task<string> GetAIResponse(string prompt)
{
var request = new
{
model = "gpt-4",
messages = new[] { new { role = "user", content = prompt } }
};
var content = new StringContent(
JsonConvert.SerializeObject(request),
Encoding.UTF8,
"application/json");
_httpClient.DefaultRequestHeaders.Authorization =
new System.Net.Http.Headers.AuthenticationHeaderValue("Bearer", _apiKey);
var response = await _httpClient.PostAsync(
"https://api.openai.com/v1/chat/completions",
content);
var responseString = await response.Content.ReadAsStringAsync();
dynamic result = JsonConvert.DeserializeObject(responseString)!;
return result.choices[0].message.content;
}
}
PR自动处理模块
csharp
public class PRProcessor
{
private readonly AIServiceClient _aiClient;
public PRProcessor(AIServiceClient aiClient) => _aiClient = aiClient;
public async Task<string> GeneratePRReview(string prDiff)
{
string prompt = $"Review this code diff and suggest improvements:\n{prDiff}\n" +
"Focus on: code quality, potential bugs, and style consistency.";
return await _aiClient.GetAIResponse(prompt);
}
public async Task<string> GeneratePRResponse(string comments)
{
string prompt = $"Respond professionally to these PR comments:\n{comments}\n" +
"Acknowledge valid points and suggest concrete action items.";
return await _aiClient.GetAIResponse(prompt);
}
}
单元测试生成模块
csharp
public class TestGenerator
{
private readonly AIServiceClient _aiClient;
public TestGenerator(AIServiceClient aiClient) => _aiClient = aiClient;
public async Task<string> GenerateUnitTest(string classCode)
{
string prompt = $"Generate xUnit tests for this C# class:\n{classCode}\n" +
"Include: happy path, edge cases, and null checks. " +
"Use Moq for dependencies mocking.";
return await _aiClient.GetAIResponse(prompt);
}
}
Bug修复模块
csharp
public class BugFixer
{
private readonly AIServiceClient _aiClient;
public BugFixer(AIServiceClient aiClient) => _aiClient = aiClient;
public async Task<string> SuggestBugFix(string errorDescription, string? codeSnippet = null)
{
string prompt = $"Propose a fix for this bug:\n{errorDescription}\n";
if (!string.IsNullOrEmpty(codeSnippet))
{
prompt += $"Relevant code:\n{codeSnippet}\n";
}
prompt += "Explain the root cause and provide the corrected code.";
return await _aiClient.GetAIResponse(prompt);
}
}
集成使用示例
csharp
// 初始化服务
var aiClient = new AIServiceClient("your-api-key");
var prProcessor = new PRProcessor(aiClient);
var testGenerator = new TestGenerator(aiClient);
var bugFixer = new BugFixer(aiClient);
// PR处理示例
var prReview = await prProcessor.GeneratePRReview("git diff output here");
// 单元测试生成示例
var testCode = await testGenerator.GenerateUnitTest("public class Calculator {...}");
// Bug修复示例
var fixSuggestion = await bugFixer.SuggestBugFix(
"NullReferenceException when user is null",
"public string GetUserName(User u) => u.Name;");
注意事项
- 需要替换
your-api-key为实际的AI服务API密钥 - 建议添加异常处理和重试机制
- 生产环境应考虑添加速率限制和缓存
- 输出的AI建议需要人工审核后再合并
- 可根据具体需求调整提示词(prompt)模板
实际实现时,可以结合GitHub API/SDK实现更完整的自动化流程,例如监听PR事件自动触发评审、关联提交与问题跟踪系统等。