‫ساخت یک دستیار کدنویسی مبتنی بر مدل زبانی محلی با استفاده از #C و NET.

curl -fsSL https://ollama.com/install.sh | sh

ollama pull codellama:latest

ollama run codellama

dotnet new console -n CodeAgent
cd CodeAgent

dotnet add package Microsoft.CodeAnalysis.CSharp
dotnet add package Spectre.Console
dotnet add package Newtonsoft.Json

public class CodeAgent
{
    private readonly LLMClient _llm;

    public CodeAgent(LLMClient llm)
    {
        _llm = llm;
    }

    public async Task AnalyzeAsync(string path)
    {
        string code = File.ReadAllText(path);
        var syntaxTree = CSharpSyntaxTree.ParseText(code);
        var root = syntaxTree.GetRoot();
        string summary = RoslynAnalyzer.Analyze(root);
        string prompt = PromptBuilder.BuildPrompt(code, summary);
        string llmResponse = await _llm.SendAsync(prompt);
        AnsiConsole.MarkupLine($"[green]Suggestion from AI:[/]\n{llmResponse}");
    }
}

public class LLMClient
{
    private readonly HttpClient _http = new();

    public async Task<string> SendAsync(string prompt)
    {
        var body = new
        {
            model = "codellama",
            prompt = prompt,
            stream = false
        };
        var response = await _http.PostAsync(
            "http://localhost:11434/api/generate",
            new StringContent(JsonConvert.SerializeObject(body), Encoding.UTF8, "application/json"));
        string json = await response.Content.ReadAsStringAsync();
        var parsed = JObject.Parse(json);
        return parsed["response"]?.ToString() ?? "No response";
    }
}

public static class RoslynAnalyzer
{
    public static string Analyze(SyntaxNode root)
    {
        var methodCount = root.DescendantNodes().OfType<MethodDeclarationSyntax>().Count();
        var classCount = root.DescendantNodes().OfType<ClassDeclarationSyntax>().Count();
        return $"This file contains {classCount} class(es) and {methodCount} method(s).";
    }
}

public static class PromptBuilder
{
    public static string BuildPrompt(string code, string summary)
    {
        return $"""
        You are an expert C# developer AI assistant.
        Here is a summary of the file:
        {summary}
        Analyze the following code for potential improvements, bugs, or best practices:
        ```
        {code}
        ```
        Provide concrete suggestions and explain why.
        """;
    }
}

class Program
{
    static async Task Main(string[] args)
    {
        if (args.Length == 0)
        {
            AnsiConsole.MarkupLine("[red]Usage:[/] dotnet run <path-to-cs-file>");
            return;
        }
        var llm = new LLMClient();
        var agent = new CodeAgent(llm);
        await agent.AnalyzeAsync(args[0]);
    }
}

dotnet run ./Example.cs