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58 lines
2.1 KiB
C#
58 lines
2.1 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to create an agent from a YAML based declarative representation.
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using Azure.AI.OpenAI;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Extensions.AI;
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var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
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// Create the chat client
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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IChatClient chatClient = new AzureOpenAIClient(
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new Uri(endpoint),
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new DefaultAzureCredential())
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.GetChatClient(deploymentName)
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.AsIChatClient();
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// Define the agent using a YAML definition.
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var text =
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"""
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kind: Prompt
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name: Assistant
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description: Helpful assistant
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instructions: You are a helpful assistant. You answer questions in the language specified by the user. You return your answers in a JSON format.
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model:
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options:
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temperature: 0.9
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topP: 0.95
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outputSchema:
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properties:
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language:
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type: string
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required: true
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description: The language of the answer.
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answer:
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type: string
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required: true
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description: The answer text.
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""";
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// Create the agent from the YAML definition.
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var agentFactory = new ChatClientPromptAgentFactory(chatClient);
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var agent = await agentFactory.CreateFromYamlAsync(text);
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// Invoke the agent and output the text result.
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Console.WriteLine(await agent!.RunAsync("Tell me a joke about a pirate in English."));
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// Invoke the agent with streaming support.
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await foreach (var update in agent!.RunStreamingAsync("Tell me a joke about a pirate in French."))
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{
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Console.WriteLine(update);
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}
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