Add one simple sync & async samples for the Deployment methods

sdk/ai/azure-ai-projects-dp1/samples/datasets/sample_datasets.py

@@ -7,7 +7,7 @@
 """
 DESCRIPTION:
     Given an AIProjectClient, this sample demonstrates how to use the synchronous
-    datasets methods to upload files, create datasets that reference those files,
+    `.datasets` methods to upload files, create datasets that reference those files,
     list datasets and delete datasets.
 
 USAGE:

sdk/ai/azure-ai-projects-dp1/samples/datasets/sample_datasets_async.py

@@ -7,7 +7,7 @@
 """
 DESCRIPTION:
     Given an AIProjectClient, this sample demonstrates how to use the asynchronous
-    datasets methods to upload files, create datasets that reference those files,
+    `.datasets` methods to upload files, create datasets that reference those files,
     list datasets and delete datasets.
 
 USAGE:

sdk/ai/azure-ai-projects-dp1/samples/deployments/sample_deployments.py

@@ -0,0 +1,49 @@
+
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+DESCRIPTION:
+    Given an AIProjectClient, this sample demonstrates how to use the synchronous
+    `.deployments` methods to enumerate AI models deployed to your AI Foundry Project.
+
+USAGE:
+    python sample_deployments.py
+
+    Before running the sample:
+
+    pip install azure-ai-projects azure-identity
+
+    Set these environment variables with your own values:
+    1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
+       Azure AI Foundry project.
+    2) DEPLOYMENT_NAME - Required. The name of the deployment to retrieve.
+    3) MODEL_PUBLISHER - Required. The publisher of the model to filter by.
+"""
+
+import os
+from azure.identity import DefaultAzureCredential
+from azure.ai.projects.dp1 import AIProjectClient
+
+endpoint = os.environ["PROJECT_ENDPOINT"]
+deployment_name = os.environ["DEPLOYMENT_NAME"]
+model_publisher = os.environ["MODEL_PUBLISHER"]
+
+project_client = AIProjectClient(
+    endpoint=endpoint,
+    credential=DefaultAzureCredential(),
+)
+
+print("List all deployments:")
+for deployment in project_client.deployments.list():
+    print(deployment)
+
+print("Get a single deployment named `f{deployment_name}`:")
+deployment = project_client.deployments.get(deployment_name)
+print(deployment)
+
+print(f"List all deployments by the model publisher `{model_publisher}`:")
+for deployment in project_client.deployments.list(model_publisher=model_publisher):
+    print(deployment)

sdk/ai/azure-ai-projects-dp1/samples/deployments/sample_deployments_async.py

@@ -0,0 +1,60 @@
+
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+DESCRIPTION:
+    Given an AIProjectClient, this sample demonstrates how to use the asynchronous
+    `.deployments` methods to enumerate AI models deployed to your AI Foundry Project.
+
+USAGE:
+    python sample_deployments_async.py
+
+    Before running the sample:
+
+    pip install azure-ai-projects azure-identity aiohttp
+
+    Set these environment variables with your own values:
+    1) PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
+       Azure AI Foundry project.
+    2) DEPLOYMENT_NAME - Required. The name of the deployment to retrieve.
+    3) MODEL_PUBLISHER - Required. The publisher of the model to filter by.       
+"""
+
+import asyncio
+import os
+from azure.identity.aio import DefaultAzureCredential
+from azure.ai.projects.dp1.aio import AIProjectClient
+
+async def sample_deployments_async() -> None:
+
+    endpoint = os.environ["PROJECT_ENDPOINT"]
+    deployment_name = os.environ["DEPLOYMENT_NAME"]
+    model_publisher = os.environ["MODEL_PUBLISHER"]
+
+    project_client = AIProjectClient(
+        endpoint=endpoint,
+        credential=DefaultAzureCredential(),
+    )
+
+    print("List all deployments:")
+    async for deployment in project_client.deployments.list():
+        print(deployment)
+
+    print("Get a single deployment named `f{deployment_name}`:")
+    deployment = await project_client.deployments.get(deployment_name)
+    print(deployment)
+
+    print(f"List all deployments by the model publisher `{model_publisher}`:")
+    async for deployment in project_client.deployments.list(model_publisher=model_publisher):
+        print(deployment)
+
+
+async def main():
+    await sample_deployments_async()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())