This repository contains various connectors and plugins for integrating Large Language Models (LLMs) via Semantic Kernel.
The Atc.SemanticKernel.Connectors.Ollama
package contains a connector for integrating with Ollama .
It supports the following capabilities by implementing the interfaces (IChatCompletionService
, ITextGenerationService
, ITextEmbeddingGenerationService
)
Note: Embedding generation is marked as experimental in Semantic Kernel
To seamlessly integrate Ollama services into your application, you can utilize the provided KernelBuilder
and ServiceCollection
extension methods. These methods simplify the setup process and ensure that the Ollama services are correctly configured and ready to use within your application's service architecture.
Both methods ensure that the Ollama services are added to the application's service collection and configured according to the specified parameters, making them available throughout your application via dependency injection.
The configuration examples below utilizes the application's settings (typically defined in appsettings.json) to configure each Ollama service with appropriate endpoints and model identifiers.
The KernelBuilder
extensions allow for fluent configuration and registration of services. Here’s how you can wire up Ollama services using KernelBuilder
:
var builder = WebApplication.CreateBuilder(args);
// Add Kernel services
builder.Services.AddKernel()
.AddOllamaTextGeneration(
builder.Configuration["Ollama:Endpoint"],
builder.Configuration["Ollama:Model"])
.AddOllamaChatCompletion(
builder.Configuration["Ollama:Endpoint"],
builder.Configuration["Ollama:Model"])
.AddOllamaTextEmbeddingGeneration(
builder.Configuration["Ollama:Endpoint"],
builder.Configuration["Ollama:Model"]);
Alternatively, if you're configuring services directly through IServiceCollection
, here's how you can add Ollama services:
var builder = WebApplication.CreateBuilder(args);
// Configure Ollama services directly
builder.Services
.AddOllamaTextGeneration(
builder.Configuration["Ollama:Endpoint"],
builder.Configuration["Ollama:Model"])
.AddOllamaChatCompletion(
builder.Configuration["Ollama:Endpoint"],
builder.Configuration["Ollama:Model"])
.AddOllamaTextEmbeddingGeneration(
builder.Configuration["Ollama:Endpoint"],
builder.Configuration["Ollama:Model"]);
To utilize the OllamaChatCompletionService
for chat completions, you can initialize it with an OllamaApiClient
or a custom API endpoint, and a model ID. Below is an example of how to use the service to handle chat sessions.
var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
var history = new ChatHistory();
// Add needed messages to current chat history
history.AddSystemMessage("...");
history.AddUserMessage(input);
var chatResponse = await chat.GetChatMessageContentsAsync(history);
Console.WriteLine(chatResponse[^1].Content);
The OllamaTextGenerationService
offers text generation capabilities using a specified model. This service can be initialized using an OllamaApiClient
or a custom API endpoint, and a model ID. Below is an example of how to use the service to handle text generation.
var textGen = kernel.GetRequiredService<ITextGenerationService>();
var response = await textGen.GetTextContentsAsync("The weather in January in Denmark is usually ");
Console.WriteLine(response[^1].Text);
The OllamaTextEmbeddingGenerationService provides functionality to generate text embeddings. This service can be initiated with an OllamaApiClient
or a custom endpoint, and model ID. Below is an example of how to use the service to handle text generation.
#pragma warning disable SKEXP0001
var embeddingGenerationService = kernel.GetRequiredService<ITextEmbeddingGenerationService>();
#pragma warning restore SKEXP0001
List<string> texts = ["Hello"];
var embeddings = await embeddingGenerationService.GenerateEmbeddingsAsync(texts);
Console.WriteLine($"Embeddings Length: {embeddings.Count}");
- .NET 8 SDK
- Ollama with one or more downloaded models