chore: import upstream snapshot with attribution

python/samples/01-get-started/01_hello_agent.py

@@ -0,0 +1,51 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import Agent
+from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
+
+"""
+Hello Agent — Simplest possible agent
+
+This sample creates a minimal agent using FoundryChatClient via an
+Azure AI Foundry project endpoint, and runs it in both non-streaming and streaming modes.
+
+There are XML tags in all of the get started samples, those are used to display the same code in the docs repo.
+"""
+
+
+async def main() -> None:
+    # <create_agent>
+    client = FoundryChatClient(
+        project_endpoint="https://your-project.services.ai.azure.com",
+        model="gpt-4o",
+        credential=AzureCliCredential(),
+    )
+
+    agent = Agent(
+        client=client,
+        name="HelloAgent",
+        instructions="You are a friendly assistant. Keep your answers brief.",
+    )
+    # </create_agent>
+
+    # <run_agent>
+    # Non-streaming: get the complete response at once
+    result = await agent.run("What is the capital of France?")
+    print(f"Agent: {result}")
+    # </run_agent>
+
+    # <run_agent_streaming>
+    # Streaming: receive tokens as they are generated
+    print("Agent (streaming): ", end="", flush=True)
+    async for chunk in agent.run("Tell me a one-sentence fun fact.", stream=True):
+        if chunk.text:
+            print(chunk.text, end="", flush=True)
+    print()
+    # </run_agent_streaming>
+
+
+if __name__ == "__main__":
+    asyncio.run(main())