Update samples and CHANGELOG to enhance memory CRUD demonstrations an… (#47267)

* Update samples and CHANGELOG to enhance memory CRUD demonstrations and clean up test samples

* Update assets.json tag and clean up skipped tests in test_samples_async.py

* Update CHANGELOG to reflect self-contained dataset generation job samples and extend memory CRUD demonstrations

Author: howieleung

sdk/ai/azure-ai-projects/CHANGELOG.md

@@ -5,7 +5,8 @@
 ### Sample updates
 
 * Added Routines samples `sample_routines_crud.py` demonstrating CRUD operations and `sample_routines_with_timer_trigger.py` demonstrating triggering a routine by a timer.
-* `samples/datasets/sample_dataset_generation_job_traces_for_evaluation.py` and `samples/datasets/sample_dataset_generation_job_traces_for_finetuning.py` are now self-contained: each sample creates a temporary agent, seeds conversations, retries the data generation job over the trace window, and cleans up all created resources.
+* `sample_dataset_generation_job_traces_for_evaluation.py` and `sample_dataset_generation_job_traces_for_finetuning.py` are now self-contained: each sample creates a temporary agent, seeds conversations, retries the data generation job over the trace window, and cleans up all created resources.
+* Extended `sample_memory_crud.py` and `sample_memory_crud_async.py` to also demonstrate memory item CRUD (`create_memory`, `get_memory`, `update_memory`, `list_memories`, `delete_memory`) in addition to memory store CRUD.
 
 ## 2.2.0 (2026-05-29)
 

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_11a3786ca2"
+  "Tag": "python/ai/azure-ai-projects_7a920efd23"
 }

sdk/ai/azure-ai-projects/samples/memories/sample_memory_crud.py

@@ -7,7 +7,12 @@
 """
 DESCRIPTION:
     This sample demonstrates how to perform CRUD operations on a memory store
-    using the synchronous AIProjectClient.
+    and on the individual memory items inside it, using the synchronous
+    AIProjectClient.
+
+    Memory store operations: create, get, update, list, delete.
+    Memory item operations:  create_memory, get_memory, update_memory,
+                             list_memories, delete_memory.
 
     See also /samples/agents/tools/sample_agent_memory_search.py that shows
     how to use the Memory Search Tool in a prompt agent.
@@ -33,54 +38,91 @@
 from azure.core.exceptions import ResourceNotFoundError
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
-from azure.ai.projects.models import MemoryStoreDefaultDefinition
+from azure.ai.projects.models import MemoryItemKind, MemoryStoreDefaultDefinition
 
 load_dotenv()
 
 endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
+memory_store_name = "my_memory_store"
+scope = "user_123"
 
 with (
     DefaultAzureCredential(exclude_interactive_browser_credential=False) as credential,
     AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
 ):
 
     # Delete memory store, if it already exists
-    memory_store_name = "my_memory_store"
     try:
         project_client.beta.memory_stores.delete(memory_store_name)
         print(f"Memory store `{memory_store_name}` deleted")
     except ResourceNotFoundError:
         pass
 
-    # Create Memory Store
-    definition = MemoryStoreDefaultDefinition(
-        chat_model=os.environ["MEMORY_STORE_CHAT_MODEL_DEPLOYMENT_NAME"],
-        embedding_model=os.environ["MEMORY_STORE_EMBEDDING_MODEL_DEPLOYMENT_NAME"],
-    )
+    # Create memory store
     memory_store = project_client.beta.memory_stores.create(
         name=memory_store_name,
         description="Example memory store for conversations",
-        definition=definition,
+        definition=MemoryStoreDefaultDefinition(
+            chat_model=os.environ["MEMORY_STORE_CHAT_MODEL_DEPLOYMENT_NAME"],
+            embedding_model=os.environ["MEMORY_STORE_EMBEDDING_MODEL_DEPLOYMENT_NAME"],
+        ),
     )
     print(f"Created memory store: {memory_store.name} ({memory_store.id}): {memory_store.description}")
 
-    # Get Memory Store
+    # Get memory store
     get_store = project_client.beta.memory_stores.get(memory_store.name)
     print(f"Retrieved: {get_store.name} ({get_store.id}): {get_store.description}")
 
-    # Update Memory Store
+    # Update memory store
     updated_store = project_client.beta.memory_stores.update(
         name=memory_store.name,
         description="Updated description",
     )
     print(f"Updated: {updated_store.name} ({updated_store.id}): {updated_store.description}")
 
-    # List Memory Store
+    # List memory stores
     memory_stores = list(project_client.beta.memory_stores.list(limit=10))
     print(f"Found {len(memory_stores)} memory stores")
     for store in memory_stores:
         print(f"  - {store.name} ({store.id}): {store.description}")
 
-    # Delete Memory Store
+    # Create a memory item
+    created_item = project_client.beta.memory_stores.create_memory(
+        memory_store.name,
+        scope=scope,
+        content="The user prefers responses in concise bullet points.",
+        kind=MemoryItemKind.USER_PROFILE,
+    )
+    print(f"Created memory item: {created_item.memory_id} (kind={created_item.kind}) -> {created_item.content}")
+
+    # Get the memory item
+    fetched_item = project_client.beta.memory_stores.get_memory(memory_store.name, created_item.memory_id)
+    print(f"Retrieved memory item: {fetched_item.memory_id} -> {fetched_item.content}")
+
+    # Update the memory item
+    updated_item = project_client.beta.memory_stores.update_memory(
+        memory_store.name,
+        fetched_item.memory_id,
+        content="The user prefers concise bullet points and Python code samples.",
+    )
+    print(f"Updated memory item: {updated_item.memory_id} -> {updated_item.content}")
+
+    # Add a second memory item, then list items in the scope
+    project_client.beta.memory_stores.create_memory(
+        memory_store.name,
+        scope=scope,
+        content="The user is working on the azure-ai-projects Python SDK.",
+        kind=MemoryItemKind.USER_PROFILE,
+    )
+    items = list(project_client.beta.memory_stores.list_memories(memory_store.name, scope=scope, limit=10))
+    print(f"Found {len(items)} memory items in scope '{scope}':")
+    for item in items:
+        print(f"  - {item.memory_id} ({item.kind}): {item.content}")
+
+    # Delete a memory item
+    delete_item_result = project_client.beta.memory_stores.delete_memory(memory_store.name, created_item.memory_id)
+    print(f"Deleted memory item {created_item.memory_id}: deleted={delete_item_result.deleted}")
+
+    # Delete the memory store
     delete_response = project_client.beta.memory_stores.delete(memory_store.name)
-    print(f"Deleted: {delete_response.deleted}")
+    print(f"Deleted memory store: {delete_response.deleted}")

sdk/ai/azure-ai-projects/samples/memories/sample_memory_crud_async.py

@@ -7,7 +7,12 @@
 """
 DESCRIPTION:
     This sample demonstrates how to perform CRUD operations on a memory store
-    using the asynchronous AIProjectClient.
+    and on the individual memory items inside it, using the asynchronous
+    AIProjectClient.
+
+    Memory store operations: create, get, update, list, delete.
+    Memory item operations:  create_memory, get_memory, update_memory,
+                             list_memories, delete_memory.
 
     See also /samples/agents/tools/sample_agent_memory_search_async.py that shows
     how to use the Memory Search Tool in a prompt agent.
@@ -34,62 +39,101 @@
 from azure.core.exceptions import ResourceNotFoundError
 from azure.identity.aio import DefaultAzureCredential
 from azure.ai.projects.aio import AIProjectClient
-from azure.ai.projects.models import MemoryStoreDefaultDefinition
-
-load_dotenv()
+from azure.ai.projects.models import MemoryItemKind, MemoryStoreDefaultDefinition
 
 
 async def main() -> None:
+    load_dotenv()
 
     endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
+    memory_store_name = "my_memory_store"
+    scope = "user_123"
 
     async with (
         DefaultAzureCredential() as credential,
         AIProjectClient(endpoint=endpoint, credential=credential) as project_client,
     ):
 
         # Delete memory store, if it already exists
-        memory_store_name = "my_memory_store"
         try:
             await project_client.beta.memory_stores.delete(memory_store_name)
             print(f"Memory store `{memory_store_name}` deleted")
         except ResourceNotFoundError:
             pass
 
-        # Create Memory Store
-        definition = MemoryStoreDefaultDefinition(
-            chat_model=os.environ["MEMORY_STORE_CHAT_MODEL_DEPLOYMENT_NAME"],
-            embedding_model=os.environ["MEMORY_STORE_EMBEDDING_MODEL_DEPLOYMENT_NAME"],
-        )
+        # Create memory store
         memory_store = await project_client.beta.memory_stores.create(
             name=memory_store_name,
             description="Example memory store for conversations",
-            definition=definition,
+            definition=MemoryStoreDefaultDefinition(
+                chat_model=os.environ["MEMORY_STORE_CHAT_MODEL_DEPLOYMENT_NAME"],
+                embedding_model=os.environ["MEMORY_STORE_EMBEDDING_MODEL_DEPLOYMENT_NAME"],
+            ),
         )
         print(f"Created memory store: {memory_store.name} ({memory_store.id}): {memory_store.description}")
 
-        # Get Memory Store
+        # Get memory store
         get_store = await project_client.beta.memory_stores.get(memory_store.name)
         print(f"Retrieved: {get_store.name} ({get_store.id}): {get_store.description}")
 
-        # Update Memory Store
+        # Update memory store
         updated_store = await project_client.beta.memory_stores.update(
             name=memory_store.name,
             description="Updated description",
         )
         print(f"Updated: {updated_store.name} ({updated_store.id}): {updated_store.description}")
 
-        # List Memory Store
-        memory_stores = []
-        async for store in project_client.beta.memory_stores.list(limit=10):
-            memory_stores.append(store)
+        # List memory stores
+        memory_stores = [store async for store in project_client.beta.memory_stores.list(limit=10)]
         print(f"Found {len(memory_stores)} memory stores")
         for store in memory_stores:
             print(f"  - {store.name} ({store.id}): {store.description}")
 
-        # Delete Memory Store
+        # Create a memory item
+        created_item = await project_client.beta.memory_stores.create_memory(
+            memory_store.name,
+            scope=scope,
+            content="The user prefers responses in concise bullet points.",
+            kind=MemoryItemKind.USER_PROFILE,
+        )
+        print(f"Created memory item: {created_item.memory_id} (kind={created_item.kind}) -> {created_item.content}")
+
+        # Get the memory item
+        fetched_item = await project_client.beta.memory_stores.get_memory(memory_store.name, created_item.memory_id)
+        print(f"Retrieved memory item: {fetched_item.memory_id} -> {fetched_item.content}")
+
+        # Update the memory item
+        updated_item = await project_client.beta.memory_stores.update_memory(
+            memory_store.name,
+            fetched_item.memory_id,
+            content="The user prefers concise bullet points and Python code samples.",
+        )
+        print(f"Updated memory item: {updated_item.memory_id} -> {updated_item.content}")
+
+        # Add a second memory item, then list items in the scope
+        await project_client.beta.memory_stores.create_memory(
+            memory_store.name,
+            scope=scope,
+            content="The user is working on the azure-ai-projects Python SDK.",
+            kind=MemoryItemKind.USER_PROFILE,
+        )
+        items = [
+            item
+            async for item in project_client.beta.memory_stores.list_memories(memory_store.name, scope=scope, limit=10)
+        ]
+        print(f"Found {len(items)} memory items in scope '{scope}':")
+        for item in items:
+            print(f"  - {item.memory_id} ({item.kind}): {item.content}")
+
+        # Delete a memory item
+        delete_item_result = await project_client.beta.memory_stores.delete_memory(
+            memory_store.name, created_item.memory_id
+        )
+        print(f"Deleted memory item {created_item.memory_id}: deleted={delete_item_result.deleted}")
+
+        # Delete the memory store
         delete_response = await project_client.beta.memory_stores.delete(memory_store.name)
-        print(f"Deleted: {delete_response.deleted}")
+        print(f"Deleted memory store: {delete_response.deleted}")
 
 
 if __name__ == "__main__":

sdk/ai/azure-ai-projects/tests/samples/test_samples.py

@@ -63,11 +63,7 @@ def test_agent_tools_samples(self, sample_path: str, **kwargs) -> None:
         "sample_path",
         get_sample_paths(
             "memories",
-            samples_to_skip=[
-                "sample_memory_advanced.py",
-                "sample_memory_basic.py",
-                "sample_memory_crud.py",  # Sample works fine. But AI thinks something is wrong.
-            ],
+            samples_to_skip=[],
         ),
     )
     @servicePreparer()

sdk/ai/azure-ai-projects/tests/samples/test_samples_async.py

@@ -51,9 +51,6 @@ async def test_agent_tools_samples_async(self, sample_path: str, **kwargs) -> No
         get_async_sample_paths(
             "memories",
             samples_to_skip=[
-                "sample_memory_advanced_async.py",
-                "sample_memory_basic_async.py",
-                "sample_memory_crud_async.py",  # Skipped until re-enabled and recorded on Foundry endpoint that supports the new versioning schema
             ],
         ),
     )