chore: import upstream snapshot with attribution

python/samples/01-get-started/04_memory.py

@@ -0,0 +1,105 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from typing import Any
+
+from agent_framework import Agent, AgentSession, ContextProvider, SessionContext
+from agent_framework.foundry import FoundryChatClient
+from azure.identity import AzureCliCredential
+
+"""
+Agent Memory with Context Providers and Session State
+
+Context providers inject dynamic context into each agent call. This sample
+shows a provider that stores the user's name in session state and personalizes
+responses — the name persists across turns via the session.
+"""
+
+
+# <context_provider>
+class UserMemoryProvider(ContextProvider):
+    """A context provider that remembers user info in session state."""
+
+    DEFAULT_SOURCE_ID = "user_memory"
+
+    def __init__(self):
+        super().__init__(self.DEFAULT_SOURCE_ID)
+
+    async def before_run(
+        self,
+        *,
+        agent: Any,
+        session: AgentSession | None,
+        context: SessionContext,
+        state: dict[str, Any],
+    ) -> None:
+        """Inject personalization instructions based on stored user info."""
+        user_name = state.get("user_name")
+        if user_name:
+            context.extend_instructions(
+                self.source_id,
+                f"The user's name is {user_name}. Always address them by name.",
+            )
+        else:
+            context.extend_instructions(
+                self.source_id,
+                "You don't know the user's name yet. Ask for it politely.",
+            )
+
+    async def after_run(
+        self,
+        *,
+        agent: Any,
+        session: AgentSession | None,
+        context: SessionContext,
+        state: dict[str, Any],
+    ) -> None:
+        """Extract and store user info in session state after each call."""
+        for msg in context.input_messages:
+            text = msg.text if hasattr(msg, "text") else ""
+            if isinstance(text, str) and "my name is" in text.lower():
+                state["user_name"] = text.lower().split("my name is")[-1].strip().split()[0].capitalize()
+
+
+# </context_provider>
+
+
+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="MemoryAgent",
+        instructions="You are a friendly assistant.",
+        context_providers=[UserMemoryProvider()],
+    )
+    # </create_agent>
+
+    # <run_with_memory>
+    session = agent.create_session()
+
+    # The provider doesn't know the user yet — it will ask for a name
+    result = await agent.run("Hello! What's the square root of 9?", session=session)
+    print(f"Agent: {result}\n")
+
+    # Now provide the name — the provider stores it in session state
+    result = await agent.run("My name is Alice", session=session)
+    print(f"Agent: {result}\n")
+
+    # Subsequent calls are personalized — name persists via session state
+    result = await agent.run("What is 2 + 2?", session=session)
+    print(f"Agent: {result}\n")
+
+    # Inspect session state to see what the provider stored
+    provider_state = session.state.get("user_memory", {})
+    print(f"[Session State] Stored user name: {provider_state.get('user_name')}")
+    # </run_with_memory>
+
+
+if __name__ == "__main__":
+    asyncio.run(main())