microsoft--semantic-kernel/dotnet/samples/Concepts/ChatCompletion/Ollama_ChatCompletion.cs

// Copyright (c) Microsoft. All rights reserved.

using System.Text;
using Microsoft.Extensions.AI;
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.ChatCompletion;
using OllamaSharp;

namespace ChatCompletion;

/// <summary>
/// These examples demonstrate different ways of using chat completion with Ollama API.
/// </summary>
public class Ollama_ChatCompletion(ITestOutputHelper output) : BaseTest(output)
{
    /// <summary>
    /// Demonstrates how you can use the chat completion service directly.
    /// </summary>
    [Fact]
    public async Task UsingChatClientPromptAsync()
    {
        Assert.NotNull(TestConfiguration.Ollama.ModelId);

        Console.WriteLine("======== Ollama - Chat Completion ========");

        using IChatClient ollamaClient = new OllamaApiClient(
            uriString: TestConfiguration.Ollama.Endpoint,
            defaultModel: TestConfiguration.Ollama.ModelId);

        Console.WriteLine("Chat content:");
        Console.WriteLine("------------------------");

        List<ChatMessage> chatHistory = [new ChatMessage(ChatRole.System, "You are a librarian, expert about books")];

        // First user message
        chatHistory.Add(new(ChatRole.User, "Hi, I'm looking for book suggestions"));
        this.OutputLastMessage(chatHistory);

        // First assistant message
        var reply = await ollamaClient.GetResponseAsync(chatHistory);
        chatHistory.AddRange(reply.Messages);
        this.OutputLastMessage(chatHistory);

        // Second user message
        chatHistory.Add(new(ChatRole.User, "I love history and philosophy, I'd like to learn something new about Greece, any suggestion"));
        this.OutputLastMessage(chatHistory);

        // Second assistant message
        reply = await ollamaClient.GetResponseAsync(chatHistory);
        chatHistory.AddRange(reply.Messages);
        this.OutputLastMessage(chatHistory);
    }

    /// <summary>
    /// Demonstrates how you can get extra information from the service response, using the underlying inner content.
    /// </summary>
    /// <remarks>
    /// This is a breaking glass scenario, any attempt on running with different versions of OllamaSharp library that introduces breaking changes
    /// may cause breaking changes in the code below.
    /// </remarks>
    [Fact]
    public async Task UsingChatCompletionServicePromptWithInnerContentAsync()
    {
        Assert.NotNull(TestConfiguration.Ollama.ModelId);

        Console.WriteLine("======== Ollama - Chat Completion ========");

        using var ollamaClient = new OllamaApiClient(
            uriString: TestConfiguration.Ollama.Endpoint,
            defaultModel: TestConfiguration.Ollama.ModelId);

        var chatService = ollamaClient.AsChatCompletionService();

        Console.WriteLine("Chat content:");
        Console.WriteLine("------------------------");

        var chatHistory = new ChatHistory("You are a librarian, expert about books");

        // First user message
        chatHistory.AddUserMessage("Hi, I'm looking for book suggestions");
        this.OutputLastMessage(chatHistory);

        // First assistant message
        var reply = await chatService.GetChatMessageContentAsync(chatHistory);

        // Assistant message details
        // Ollama Sharp does not support non-streaming and always perform streaming calls, for this reason, the inner content is always a list of chunks.
        var ollamaSharpInnerContent = reply.InnerContent as OllamaSharp.Models.Chat.ChatDoneResponseStream;

        OutputOllamaSharpContent(ollamaSharpInnerContent!);
    }

    /// <summary>
    /// Demonstrates how you can template a chat history call using the kernel for invocation.
    /// </summary>
    [Fact]
    public async Task ChatPromptAsync()
    {
        Assert.NotNull(TestConfiguration.Ollama.ModelId);

        StringBuilder chatPrompt = new("""
                                       <message role="system">You are a librarian, expert about books</message>
                                       <message role="user">Hi, I'm looking for book suggestions</message>
                                       """);

        var kernel = Kernel.CreateBuilder()
            .AddOllamaChatClient(
                endpoint: new Uri(TestConfiguration.Ollama.Endpoint ?? "http://localhost:11434"),
                modelId: TestConfiguration.Ollama.ModelId)
            .Build();

        var reply = await kernel.InvokePromptAsync(chatPrompt.ToString());

        chatPrompt.AppendLine($"<message role=\"assistant\"><![CDATA[{reply}]]></message>");
        chatPrompt.AppendLine("<message role=\"user\">I love history and philosophy, I'd like to learn something new about Greece, any suggestion</message>");

        reply = await kernel.InvokePromptAsync(chatPrompt.ToString());

        Console.WriteLine(reply);
    }

    /// <summary>
    /// Demonstrates how you can template a chat history call and get extra information from the response while using the kernel for invocation.
    /// </summary>
    /// <remarks>
    /// This is a breaking glass scenario, any attempt on running with different versions of OllamaSharp library that introduces breaking changes
    /// may cause breaking changes in the code below.
    /// </remarks>
    [Fact]
    public async Task ChatPromptWithInnerContentAsync()
    {
        Assert.NotNull(TestConfiguration.Ollama.ModelId);

        StringBuilder chatPrompt = new("""
                                       <message role="system">You are a librarian, expert about books</message>
                                       <message role="user">Hi, I'm looking for book suggestions</message>
                                       """);

        var kernel = Kernel.CreateBuilder()
            .AddOllamaChatClient(
                endpoint: new Uri(TestConfiguration.Ollama.Endpoint ?? "http://localhost:11434"),
                modelId: TestConfiguration.Ollama.ModelId)
            .Build();

        var functionResult = await kernel.InvokePromptAsync(chatPrompt.ToString());

        // Ollama Sharp does not support non-streaming and always perform streaming calls, for this reason, the inner content of a non-streaming result is a list of the generated chunks.
        var messageContent = functionResult.GetValue<ChatResponse>(); // Retrieves underlying chat message content from FunctionResult.
        var ollamaSharpRawRepresentation = messageContent!.RawRepresentation as OllamaSharp.Models.Chat.ChatDoneResponseStream; // Retrieves inner content from ChatMessageContent.

        OutputOllamaSharpContent(ollamaSharpRawRepresentation!);
    }

    /// <summary>
    /// Retrieve extra information from the final response.
    /// </summary>
    /// <param name="innerContent">The complete OllamaSharp response provided as inner content of a chat message</param>
    /// <remarks>
    /// This is a breaking glass scenario, any attempt on running with different versions of OllamaSharp library that introduces breaking changes
    /// may cause breaking changes in the code below.
    /// </remarks>
    private void OutputOllamaSharpContent(OllamaSharp.Models.Chat.ChatDoneResponseStream innerContent)
    {
        Console.WriteLine($$"""
            Model: {{innerContent.Model}}
            Message role: {{innerContent.Message.Role}}
            Message content: {{innerContent.Message.Content}}
            Created at: {{innerContent.CreatedAt}}
            Done: {{innerContent.Done}}
            Done Reason: {{innerContent.DoneReason}}
            Eval count: {{innerContent.EvalCount}}
            Eval duration: {{innerContent.EvalDuration}}
            Load duration: {{innerContent.LoadDuration}}
            Total duration: {{innerContent.TotalDuration}}
            Prompt eval count: {{innerContent.PromptEvalCount}}
            Prompt eval duration: {{innerContent.PromptEvalDuration}}
            ------------------------
            """);
    }
}