Step 3: Multi-Turn Conversations

Use a session to maintain conversation context so the agent remembers what was said earlier.

Use AgentSession to maintain context across multiple calls:

using System;
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;

var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT")
    ?? throw new InvalidOperationException("Set AZURE_OPENAI_ENDPOINT");
var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

AIAgent agent = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential())
    .AsAIAgent(
        model: deploymentName,
        instructions: "You are a friendly assistant. Keep your answers brief.",
        name: "ConversationAgent");

// Create a session to maintain conversation history
AgentSession session = await agent.CreateSessionAsync();

// First turn
Console.WriteLine(await agent.RunAsync("My name is Alice and I love hiking.", session));

// Second turn — the agent remembers the user's name and hobby
Console.WriteLine(await agent.RunAsync("What do you remember about me?", session));

Warning

DefaultAzureCredential is convenient for development but requires careful consideration in production. In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid latency issues, unintended credential probing, and potential security risks from fallback mechanisms.

Tip

See here for a full runnable sample application.

Use AgentSession to maintain context across multiple calls:

client = FoundryChatClient(
    project_endpoint="https://your-project.services.ai.azure.com",
    model="gpt-4o",
    credential=AzureCliCredential(),
)

agent = Agent(
    client=client,
    name="ConversationAgent",
    instructions="You are a friendly assistant. Keep your answers brief.",
)

# Create a session to maintain conversation history
session = agent.create_session()

# First turn
result = await agent.run("My name is Alice and I love hiking.", session=session)
print(f"Agent: {result}\n")

# Second turn — the agent should remember the user's name and hobby
result = await agent.run("What do you remember about me?", session=session)
print(f"Agent: {result}")

Tip

See the full sample for the complete runnable file.

Next steps

Step 4: Memory & Persistence

Go deeper:

• Multi-turn conversations — advanced conversation patterns
• Middleware — intercept and modify agent interactions