Add sample demonstrating per-user Prompt Agent isolation with delegat…

sdk/ai/azure-ai-projects/assets.json

@@ -2,5 +2,5 @@
   "AssetsRepo": "Azure/azure-sdk-assets",
   "AssetsRepoPrefixPath": "python",
   "TagPrefix": "python/ai/azure-ai-projects",
-  "Tag": "python/ai/azure-ai-projects_762155b7e7"
+  "Tag": "python/ai/azure-ai-projects_868fa087a5"
 }

sdk/ai/azure-ai-projects/samples/agents/sample_agent_user_identity_isolation.py

@@ -0,0 +1,101 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+DESCRIPTION:
+    This sample demonstrates per-user Prompt Agent isolation while sending
+    delegated end-user identities in the `x-ms-user-identity` header.
+
+    It invokes the same Prompt Agent as two different delegated users. Each
+    user gets a separate response chain, and the sample shows
+    that each follow-up request continues only that user's own prior math
+    context:
+
+    * First delegated user: "1 + 1 = ?" then "+ 10" -> 12
+    * Second delegated user: "2 + 2 = ?" then "+ 10" -> 14
+
+USAGE:
+    python sample_agent_user_identity_isolation.py
+
+    Before running the sample:
+
+    pip install "azure-ai-projects>=2.3.0" python-dotenv
+
+    Set these environment variables with your own values:
+    1) FOUNDRY_PROJECT_ENDPOINT - The Azure AI Project endpoint.
+    2) FOUNDRY_MODEL_NAME - The deployment name of the AI model.
+"""
+
+import os
+from uuid import uuid4
+
+from dotenv import load_dotenv
+
+from azure.identity import DefaultAzureCredential
+
+from azure.ai.projects import AIProjectClient
+from azure.ai.projects.models import PromptAgentDefinition
+
+load_dotenv()
+
+endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
+delegated_user_identity = str(uuid4())
+delegated_user_identity_2 = str(uuid4())
+
+with (
+    DefaultAzureCredential() as credential,
+    AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
+    project_client.get_openai_client() as openai_client,
+):
+    agent = project_client.agents.create_version(
+        agent_name="DelegatedUserAgent",
+        definition=PromptAgentDefinition(
+            model=os.environ["FOUNDRY_MODEL_NAME"],
+            instructions=(
+                "You are a helpful assistant that answers arithmetic questions. "
+                "Use the prior response context to resolve follow-up math questions like 'then + 10'."
+            ),
+        ),
+    )
+    print(f"Agent created (id: {agent.id}, name: {agent.name}, version: {agent.version})")
+    print(f"User 1: {delegated_user_identity}")
+    print(f"User 2: {delegated_user_identity_2}")
+
+    print("User 1 input: 1 + 1 = ?")
+    response = openai_client.responses.create(
+        input="1 + 1 = ?",
+        extra_headers={"x-ms-user-identity": delegated_user_identity},
+        extra_body={"agent_reference": {"name": agent.name, "type": "agent_reference"}},
+    )
+    print(f"Agent: {response.output_text}")
+
+    print("User 2 input: 2 + 2 = ?")
+    response_2 = openai_client.responses.create(
+        input="2 + 2 = ?",
+        extra_headers={"x-ms-user-identity": delegated_user_identity_2},
+        extra_body={"agent_reference": {"name": agent.name, "type": "agent_reference"}},
+    )
+    print(f"Agent: {response_2.output_text}")
+
+    print("User 1 input: then + 10")
+    response = openai_client.responses.create(
+        input="then + 10",
+        previous_response_id=response.id,
+        extra_headers={"x-ms-user-identity": delegated_user_identity},
+        extra_body={"agent_reference": {"name": agent.name, "type": "agent_reference"}},
+    )
+    print(f"Agent: {response.output_text}")
+
+    print("User 2 input: then + 10")
+    response_2 = openai_client.responses.create(
+        input="then + 10",
+        previous_response_id=response_2.id,
+        extra_headers={"x-ms-user-identity": delegated_user_identity_2},
+        extra_body={"agent_reference": {"name": agent.name, "type": "agent_reference"}},
+    )
+    print(f"Agent: {response_2.output_text}")
+
+    project_client.agents.delete_version(agent_name=agent.name, agent_version=agent.version)
+    print("Agent deleted")