// Copyright (c) Microsoft. All rights reserved. using Azure.Core; using Azure.Identity; using Microsoft.Extensions.DependencyInjection; using Microsoft.SemanticKernel; using Microsoft.SemanticKernel.Agents; using Microsoft.SemanticKernel.Agents.OpenAI; using Microsoft.SemanticKernel.ChatCompletion; using OpenAI; namespace GettingStarted.OpenAIAssistants; /// /// This example demonstrates how to declaratively create instances of . /// public class Step07_Assistant_Declarative : BaseAssistantTest { /// /// Demonstrates creating and using a OpenAI Assistant using configuration. /// [Fact] public async Task OpenAIAssistantAgentWithConfigurationForOpenAI() { var text = """ type: openai_assistant name: MyAgent description: My helpful agent. instructions: You are helpful agent. model: id: ${OpenAI:ChatModelId} connection: type: openai api_key: ${OpenAI:ApiKey} """; OpenAIAssistantAgentFactory factory = new(); var agent = await factory.CreateAgentFromYamlAsync(text, configuration: TestConfiguration.ConfigurationRoot); await InvokeAgentAsync(agent!, "Could you please create a bar chart for the operating profit using the following data and provide the file to me? Company A: $1.2 million, Company B: $2.5 million, Company C: $3.0 million, Company D: $1.8 million"); } /// /// Demonstrates creating and using a OpenAI Assistant using configuration for Azure OpenAI. /// [Fact] public async Task OpenAIAssistantAgentWithConfigurationForAzureOpenAI() { var text = """ type: openai_assistant name: MyAgent description: My helpful agent. instructions: You are helpful agent. model: id: ${AzureOpenAI:ChatModelId} connection: type: azure_openai endpoint: ${AzureOpenAI:Endpoint} """; OpenAIAssistantAgentFactory factory = new(); var builder = Kernel.CreateBuilder(); builder.Services.AddSingleton(new AzureCliCredential()); var kernel = builder.Build(); var agent = await factory.CreateAgentFromYamlAsync(text, new() { Kernel = kernel }, TestConfiguration.ConfigurationRoot); await InvokeAgentAsync(agent!, "Could you please create a bar chart for the operating profit using the following data and provide the file to me? Company A: $1.2 million, Company B: $2.5 million, Company C: $3.0 million, Company D: $1.8 million"); } /// /// Demonstrates creating and using a OpenAI Assistant using a Kernel. /// [Fact] public async Task OpenAIAssistantAgentWithKernel() { var text = """ type: openai_assistant name: StoryAgent description: Story Telling Agent instructions: Tell a story suitable for children about the topic provided by the user. model: id: ${AzureOpenAI:ChatModelId} """; OpenAIAssistantAgentFactory factory = new(); var agent = await factory.CreateAgentFromYamlAsync(text, new() { Kernel = this._kernel }, configuration: TestConfiguration.ConfigurationRoot); await InvokeAgentAsync(agent!, "Cats and Dogs"); } /// /// Demonstrates loading an existing OpenAI Assistant. /// [Fact] public async Task OpenAIAssistantAgentWithId() { var text = """ id: ${AzureOpenAI:AgentId} type: openai_assistant name: StoryAgent instructions: Tell a story suitable for children about the topic provided by the user. You always respond in French. """; OpenAIAssistantAgentFactory factory = new(); var agent = await factory.CreateAgentFromYamlAsync(text, new() { Kernel = this._kernel }, configuration: TestConfiguration.ConfigurationRoot); await InvokeAgentAsync(agent!, "Cats and Dogs", deleteAgent: false); } /// /// Demonstrates creating and using a OpenAI Assistant with templated instructions. /// [Fact] public async Task OpenAIAssistantAgentWithTemplate() { var text = """ type: openai_assistant name: StoryAgent description: A agent that generates a story about a topic. instructions: Tell a story about {{$topic}} that is {{$length}} sentences long. model: id: ${AzureOpenAI:ChatModelId} inputs: topic: description: The topic of the story. required: true default: Cats length: description: The number of sentences in the story. required: true default: 2 outputs: output1: description: output1 description template: format: semantic-kernel """; OpenAIAssistantAgentFactory factory = new(); var promptTemplateFactory = new KernelPromptTemplateFactory(); var agent = await factory.CreateAgentFromYamlAsync(text, new() { Kernel = this._kernel, PromptTemplateFactory = promptTemplateFactory }, TestConfiguration.ConfigurationRoot); Assert.NotNull(agent); var options = new AgentInvokeOptions() { KernelArguments = new() { { "topic", "Dogs" }, { "length", "3" }, } }; AgentThread? agentThread = null; try { await foreach (var response in agent.InvokeAsync(Array.Empty(), agentThread, options)) { agentThread = response.Thread; this.WriteAgentChatMessage(response); } } finally { var openaiAgent = agent as OpenAIAssistantAgent; Assert.NotNull(openaiAgent); await openaiAgent.Client.DeleteAssistantAsync(openaiAgent.Id); if (agentThread is not null) { await agentThread.DeleteAsync(); } } } public Step07_Assistant_Declarative(ITestOutputHelper output) : base(output) { var builder = Kernel.CreateBuilder(); builder.Services.AddSingleton(this.Client); this._kernel = builder.Build(); } #region private private readonly Kernel _kernel; /// /// Invoke the agent with the user input. /// private async Task InvokeAgentAsync(Agent agent, string input, bool deleteAgent = true) { AgentThread? agentThread = null; try { await foreach (AgentResponseItem response in agent.InvokeAsync(new ChatMessageContent(AuthorRole.User, input))) { agentThread = response.Thread; WriteAgentChatMessage(response); } } catch (Exception e) { Console.WriteLine($"Error invoking agent: {e.Message}"); } finally { if (deleteAgent) { var openaiAgent = (OpenAIAssistantAgent)agent; await openaiAgent.Client.DeleteAssistantAsync(openaiAgent.Id); } if (agentThread is not null) { await agentThread.DeleteAsync(); } } } #endregion }