Intelligent Chatbotsfor .NET Applications.

using LMKit.Model;
using LMKit.Agents;
using LMKit.TextGeneration;

// Load chat and embedding models
var chatModel = LM.LoadFromModelID("qwen3-8b");
var embedModel = LM.LoadFromModelID("bge-small-en");

// Create persistent memory
var memory = new AgentMemory(embedModel);

// Store user preferences
await memory.SaveInformationAsync(
    "user_prefs", "User prefers concise responses.",
    "style", MemoryType.Semantic);

// Create conversation with memory attached
var chat = new MultiTurnConversation(chatModel) { Memory = memory };

// Memory is recalled automatically when relevant
var response = chat.Submit("Explain dependency injection.");

using LMKit.Model;
using LMKit.TextGeneration;
using LMKit.FunctionCalling;

public class WeatherTools
{
    [LMFunction("Get current weather for a city")]
    public static string GetWeather(string city)
    {
        return $"Weather in {city}: 72°F, sunny";
    }
}

var model = LM.LoadFromModelID("qwen3-8b");
var chat = new MultiTurnConversation(model);

// Register tools from a class
chat.Tools.ImportFunctions(typeof(WeatherTools));

// Model calls GetWeather when appropriate
var response = chat.Submit("What's the weather in Tokyo?");