🖥️ LM Studio — Local AI

using Microsoft.Agents.AI;
using OpenAI;
using System.ClientModel;

// 1. Read LM Studio server settings from environment variables.
var endpoint  = Environment.GetEnvironmentVariable("LMS_ENDPOINT")
                ?? throw new InvalidOperationException("LMS_ENDPOINT is not set.");
var modelName = Environment.GetEnvironmentVariable("LMS_MODEL")
                ?? throw new InvalidOperationException("LMS_MODEL is not set.");

// 2. Create a standard OpenAIClient pointed at the local LM Studio server.
//    A real API key is not required — pass any non-empty placeholder string.
AIAgent agent = new OpenAIClient(
        new ApiKeyCredential("lmstudio"),
        new OpenAIClientOptions { Endpoint = new Uri(endpoint) })
    .GetChatClient(modelName)
    .AsAIAgent(
        instructions: "You are a helpful assistant running locally via LM Studio.",
        name: "LocalAgent");

// 3. Same RunAsync() API as any other AIAgent — provider is transparent.
Console.WriteLine(await agent.RunAsync("What is the capital of Japan?"));

using Microsoft.Agents.AI;
using OpenAI;
using System.ClientModel;

var endpoint  = Environment.GetEnvironmentVariable("LMS_ENDPOINT")!;
var modelName = Environment.GetEnvironmentVariable("LMS_MODEL")!;

AIAgent agent = new OpenAIClient(
        new ApiKeyCredential("lmstudio"),
        new OpenAIClientOptions { Endpoint = new Uri(endpoint) })
    .GetChatClient(modelName)
    .AsAIAgent(instructions: "You are a helpful assistant.", name: "StreamAgent");

// RunStreamingAsync works identically to cloud providers — tokens arrive in real time.
Console.Write("Agent: ");
await foreach (var update in agent.RunStreamingAsync("Explain how a transformer neural network works."))
{
    if (update.Text is not null)
    {
        Console.Write(update.Text);
    }
}
Console.WriteLine();

using System.ComponentModel;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
using OpenAI;
using System.ClientModel;

var endpoint  = Environment.GetEnvironmentVariable("LMS_ENDPOINT")!;
var modelName = Environment.GetEnvironmentVariable("LMS_MODEL")!;

// Define tool functions — identical pattern to Azure OpenAI.
string GetWeather(
    [Description("The city to look up weather for")] string city)
    => $"The weather in {city} is 18°C and mostly sunny.";

string GetStockPrice(
    [Description("The ticker symbol, e.g. MSFT")] string ticker)
    => $"{ticker} is trading at $142.50 (+1.2% today).";

AIAgent agent = new OpenAIClient(
        new ApiKeyCredential("lmstudio"),
        new OpenAIClientOptions { Endpoint = new Uri(endpoint) })
    .GetChatClient(modelName)
    .AsAIAgent(
        instructions: "You are a helpful assistant. Use tools to answer accurately.",
        name: "ToolAgent",
        tools: [
            AIFunctionFactory.Create(GetWeather),
            AIFunctionFactory.Create(GetStockPrice)
        ]);

Console.WriteLine(await agent.RunAsync(
    "What's the weather in Berlin and what's the Microsoft stock price?"));

using Microsoft.Agents.AI;
using OpenAI;
using System.ClientModel;

var endpoint  = Environment.GetEnvironmentVariable("LMS_ENDPOINT")!;
var modelName = Environment.GetEnvironmentVariable("LMS_MODEL")!;

AIAgent agent = new OpenAIClient(
        new ApiKeyCredential("lmstudio"),
        new OpenAIClientOptions { Endpoint = new Uri(endpoint) })
    .GetChatClient(modelName)
    .AsAIAgent(instructions: "You are a friendly cooking assistant.", name: "ChefAgent");

// AgentSession tracks conversation history across turns automatically.
await using AgentSession session = agent.CreateSession();

Console.WriteLine(await session.RunAsync("I want to make pasta tonight. What should I know?"));
Console.WriteLine(await session.RunAsync("What sauce would you suggest for a beginner?"));
Console.WriteLine(await session.RunAsync("How long should I cook it for?"));

using System.ComponentModel;
using Microsoft.Agents.AI;
using OpenAI;
using System.ClientModel;

var endpoint  = Environment.GetEnvironmentVariable("LMS_ENDPOINT")!;
var modelName = Environment.GetEnvironmentVariable("LMS_MODEL")!;

// Agent Framework auto-generates a JSON schema from this C# record.
record BookSummary(
    [property: Description("The book title")] string Title,
    [property: Description("The author's full name")] string Author,
    [property: Description("Publication year as a 4-digit integer")] int Year,
    [property: Description("A one-sentence summary of the book's main theme")] string Theme,
    [property: Description("A genre label such as 'fiction', 'non-fiction', or 'sci-fi'")] string Genre);

AIAgent agent = new OpenAIClient(
        new ApiKeyCredential("lmstudio"),
        new OpenAIClientOptions { Endpoint = new Uri(endpoint) })
    .GetChatClient(modelName)
    .AsAIAgent(
        instructions: "You are a literary expert. Respond only with valid JSON matching the schema.",
        name: "BookAgent");

BookSummary book = await agent.RunAsync<BookSummary>(
    "Summarise '1984' by George Orwell in structured form.");

Console.WriteLine($"Title:  {book.Title} by {book.Author} ({book.Year})");
Console.WriteLine($"Genre:  {book.Genre}");
Console.WriteLine($"Theme:  {book.Theme}");