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westey
e224f06e60
* Update models used in dotnet samples to gpt-5.4-mini * Fix additional missed sample
27 lines
1.5 KiB
C#
27 lines
1.5 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample shows how to create a multi-turn conversation agent using sessions.
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// Context is preserved across multiple runs via response ID chaining in the session.
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using Azure.AI.Projects;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
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string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
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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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AIAgent agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
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.AsAIAgent(deploymentName, instructions: "You are good at telling jokes.", name: "JokerAgent");
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// Create a session to maintain context across multiple runs.
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AgentSession session = await agent.CreateSessionAsync();
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// First turn
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Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session));
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// Second turn — the agent remembers the first turn via the session.
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Console.WriteLine(await agent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", session));
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