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# ------------------------------------
# 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) MODEL_DEPLOYMENT_NAME - Required. The name of the deployment to retrieve.
3) MODEL_PUBLISHER - Optional. The publisher of the model to filter by.
4) MODEL_NAME - Optional. The name of the model to filter by.
"""
import os
from azure.identity import DefaultAzureCredential
from azure.ai.projects import AIProjectClient
endpoint = os.environ["PROJECT_ENDPOINT"]
model_deployment_name = os.environ["MODEL_DEPLOYMENT_NAME"]
model_publisher = os.environ.get("MODEL_PUBLISHER", "Microsoft")
model_name = os.environ.get("MODEL_NAME", "Phi-4")
with DefaultAzureCredential(exclude_interactive_browser_credential=False) as credential:
with AIProjectClient(endpoint=endpoint, credential=credential) as project_client:
# [START deployments_sample]
print("List all deployments:")
for deployment in project_client.deployments.list():
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)
print(f"List all deployments of model `{model_name}`:")
for deployment in project_client.deployments.list(model_name=model_name):
print(deployment)
print(f"Get a single deployment named `{model_deployment_name}`:")
deployment = project_client.deployments.get(model_deployment_name)
print(deployment)
# [END deployments_sample]
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