SpongeEngine.LMStudioSharp 1.1.0

LMStudioSharp

C# client for interacting with LM Studio through its native and OpenAI-compatible endpoints.

Features

• Complete support for LM Studio's native API
• OpenAI-compatible API endpoint support
• Text completion and chat completion
• Streaming support for both completion types
• Text embeddings generation
• Model information retrieval
• Comprehensive configuration options
• Built-in error handling and logging
• Cross-platform compatibility
• Full async/await support

📦 View Package on NuGet

Installation

Install via NuGet:

dotnet add package SpongeEngine.LMStudioSharp

Quick Start

Using Native API

using SpongeEngine.LMStudioSharp.Client;
using SpongeEngine.LMStudioSharp.Models.Base;
using SpongeEngine.LMStudioSharp.Models.Completion;
using SpongeEngine.LMStudioSharp.Models.Chat;

// Configure the client
var options = new Options
{
    BaseUrl = "http://localhost:1234",
    TimeoutSeconds = 600
};

// Create client instance
using var client = new LmStudioSharpClient(options);

// List available models
var models = await client.ListModelsAsync();
var modelId = models.Data[0].Id;

// Text completion
var completionRequest = new CompletionRequest
{
    Model = modelId,
    Prompt = "Write a short story about a robot:",
    MaxTokens = 200,
    Temperature = 0.7f,
    TopP = 0.9f
};

var completionResponse = await client.CompleteAsync(completionRequest);
Console.WriteLine(completionResponse.Choices[0].Text);

// Chat completion
var chatRequest = new ChatRequest
{
    Model = modelId,
    Messages = new List<ChatMessage>
    {
        new() { Role = "system", Content = "You are a helpful assistant." },
        new() { Role = "user", Content = "Tell me a joke about programming." }
    },
    Temperature = 0.7f
};

var chatResponse = await client.ChatCompleteAsync(chatRequest);
Console.WriteLine(chatResponse.Choices[0].Message.Content);

// Stream completion
await foreach (var token in client.StreamCompletionAsync(completionRequest))
{
    Console.Write(token);
}

Using OpenAI-Compatible API

var options = new Options
{
    BaseUrl = "http://localhost:1234",
    UseOpenAiApi = true
};

using var client = new LmStudioSharpClient(options);

// Simple completion
string response = await client.CompleteWithOpenAiAsync(
    "Write a short story about:",
    new CompletionOptions
    {
        MaxTokens = 200,
        Temperature = 0.7f
    });

// Stream completion
await foreach (var token in client.StreamCompletionWithOpenAiAsync(
    "Once upon a time...",
    new CompletionOptions { MaxTokens = 200 }))
{
    Console.Write(token);
}

Configuration Options

Basic Options

var options = new Options
{
    BaseUrl = "http://localhost:1234",    // LM Studio server URL
    ApiVersion = "v1",                    // API version
    ApiKey = "optional_api_key",          // Optional API key
    TimeoutSeconds = 600,                 // Request timeout
    UseOpenAiApi = false                  // Use OpenAI-compatible API
};

Completion Request Parameters

var request = new CompletionRequest
{
    Model = "model-id",
    Prompt = "Your prompt here",
    MaxTokens = 200,                      // Maximum tokens to generate
    Temperature = 0.7f,                   // Randomness (0.0-1.0)
    TopP = 0.9f,                          // Nucleus sampling threshold
    Stop = new[] { "\n" },               // Stop sequences
    Stream = false                        // Enable streaming
};

Error Handling

try
{
    var response = await client.CompleteAsync(request);
}
catch (SpongeEngine.LMStudioSharp.Models.Exception ex)
{
    Console.WriteLine($"LM Studio error: {ex.Message}");
    Console.WriteLine($"Provider: {ex.Provider}");
    if (ex.StatusCode.HasValue)
    {
        Console.WriteLine($"Status code: {ex.StatusCode}");
    }
    if (ex.ResponseContent != null)
    {
        Console.WriteLine($"Response content: {ex.ResponseContent}");
    }
}
catch (Exception ex)
{
    Console.WriteLine($"General error: {ex.Message}");
}

Logging

The client supports Microsoft.Extensions.Logging:

ILogger logger = LoggerFactory
    .Create(builder => builder
        .AddConsole()
        .SetMinimumLevel(LogLevel.Debug))
    .CreateLogger<LmStudioSharpClient>();

var client = new LmStudioSharpClient(options, logger);

JSON Serialization

Custom JSON settings can be provided:

var jsonSettings = new JsonSerializerSettings
{
    NullValueHandling = NullValueHandling.Ignore,
    DefaultValueHandling = DefaultValueHandling.Ignore
};

var client = new LmStudioSharpClient(options, logger: null, jsonSettings: jsonSettings);

Testing

The library includes both unit and integration tests. Integration tests require a running LM Studio server.

To run the tests:

dotnet test

To configure the test environment:

// Set environment variables for testing
Environment.SetEnvironmentVariable("LMSTUDIO_BASE_URL", "http://localhost:1234");
Environment.SetEnvironmentVariable("LMSTUDIO_OPENAI_BASE_URL", "http://localhost:1234/v1");

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues and feature requests, please use the GitHub issues page.