OllamaSharp

The easiest way to use Ollama in .NET

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OllamaSharp is a .NET binding for the Ollama API, providing an intuitive API client to interact with Ollama. It offers support for all Ollama API endpoints, real-time streaming, progress reporting, and an API console for remote management. Users can easily set up the client, list models, pull models with progress feedback, stream completions, and build interactive chats. The project includes a demo console for exploring and managing the Ollama host.

README:

OllamaSharp 🦙

OllamaSharp provides .NET bindings for the Ollama API, simplifying interactions with Ollama both locally and remotely.

🏆 Recommended by Microsoft

Features

Ease of use: Interact with Ollama in just a few lines of code.
Reliability: Powering Microsoft Semantic Kernel, .NET Aspire and Microsoft.Extensions.AI
API coverage: Covers every single Ollama API endpoint, including chats, embeddings, listing models, pulling and creating new models, and more.
Real-time streaming: Stream responses directly to your application.
Progress reporting: Real-time progress feedback on tasks like model pulling.
Tools engine: Sophisticated tool support with source generators.
Multi modality: Support for vision models.
Native AOT support: Opt-in support for Native AOT for improved performance.

Usage

OllamaSharp wraps each Ollama API endpoint in awaitable methods that fully support response streaming.

The following list shows a few simple code examples.

ℹ Try our full featured demo application that's included in this repository

Initializing

// set up the client
var uri = new Uri("http://localhost:11434");
var ollama = new OllamaApiClient(uri);

// select a model which should be used for further operations
ollama.SelectedModel = "llama3.1:8b";

Native AOT Support

For .NET Native AOT scenarios, create a custom JsonSerializerContext with your types and pass it into the constructor.

[JsonSerializable(typeof(MyCustomType))]
public partial class MyJsonContext : JsonSerializerContext { }

// Use the static factory method for NativeAOT
var ollama = new OllamaApiClient(uri, "llama3.1:8b", MyJsonContext.Default);

See the Native AOT documentation for detailed guidance.

Listing all models that are available locally

var models = await ollama.ListLocalModelsAsync();

Pulling a model and reporting progress

await foreach (var status in ollama.PullModelAsync("llama3.1:405b"))
    Console.WriteLine($"{status.Percent}% {status.Status}");

Generating a completion directly into the console

await foreach (var stream in ollama.GenerateAsync("How are you today?"))
    Console.Write(stream.Response);

Building interactive chats

// messages including their roles and tool calls will automatically be tracked within the chat object
// and are accessible via the Messages property

var chat = new Chat(ollama);

while (true)
{
    var message = Console.ReadLine();
    await foreach (var answerToken in chat.SendAsync(message))
        Console.Write(answerToken);
}

Usage with Microsoft.Extensions.AI

Microsoft built an abstraction library to streamline the usage of different AI providers. This is a really interesting concept if you plan to build apps that might use different providers, like ChatGPT, Claude and local models with Ollama.

I encourage you to read their accouncement Introducing Microsoft.Extensions.AI Preview – Unified AI Building Blocks for .NET.

OllamaSharp is the first full implementation of their IChatClient and IEmbeddingGenerator that makes it possible to use Ollama just like every other chat provider.

To do this, simply use the OllamaApiClient as IChatClient instead of IOllamaApiClient.

// install package Microsoft.Extensions.AI.Abstractions

private static IChatClient CreateChatClient(Arguments arguments)
{
  if (arguments.Provider.Equals("ollama", StringComparison.OrdinalIgnoreCase))
    return new OllamaApiClient(arguments.Uri, arguments.Model);
  else
    return new OpenAIChatClient(new OpenAI.OpenAIClient(arguments.ApiKey), arguments.Model); // ChatGPT or compatible
}

The OllamaApiClient implements both interfaces from Microsoft.Extensions.AI, you just need to cast it accordingly:

IChatClient for model inference
IEmbeddingGenerator<string, Embedding<float>> for embedding generation

Thanks

I would like to thank all the contributors who take the time to improve OllamaSharp. First and foremost mili-tan, who always keeps OllamaSharp in sync with the Ollama API.

The icon and name were reused from the amazing Ollama project.

Special thanks to JetBrains for supporting this project.

For Tasks:

Click tags to check more tools for each tasks

manage models stream completions build chats list models pull models

For Jobs:

software developer ai engineer data scientist web developer machine learning engineer

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