Update Projects SDK samples to read .env file (#43465)

Author: dargilco

sdk/ai/azure-ai-projects/azure_ai_projects_tests.template.env renamed to sdk/ai/azure-ai-projects/.env.template

@@ -1,15 +1,20 @@
 #
-# Environment variables that define secrets required for running tests.
+# Environment variables that define secrets required for running tests and samples.
 #
 # All values should be empty by default in this template.
 #
 # To run tests locally on your device:
-# 1. Rename the file to azure_ai_projects_tests.env
+# 1. Rename the file to `.env.template` to `.env`
 # 2. Fill in the values for the environment variables below (do not commit these changes to the repository!)
-# 3. Run the test (`pytest`)
+# 3. Run the tests (`pytest`) or run samples in the `samples` folder
 #
 
+# Used in samples
 # Project endpoint has the format: 
 #  `https://<your-ai-services-account-name>.services.ai.azure.com/api/projects/<your-project-name>`
+AZURE_AI_PROJECT_ENDPOINT=
+AZURE_AI_MODEL_DEPLOYMENT_NAME=
+
+# Used in tests
 AZURE_AI_PROJECTS_TESTS_PROJECT_ENDPOINT=
 

sdk/ai/azure-ai-projects/dev_requirements.txt

@@ -2,5 +2,6 @@
 ../../core/azure-core
 ../../identity/azure-identity
 aiohttp
+python-dotenv
 azure.ai.inference
 openai

sdk/ai/azure-ai-projects/samples/agents/sample_agents.py

@@ -15,21 +15,24 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity
+    pip install azure-ai-projects azure-identity python-dotenv
 
-    Set this environment variables with your own values:
-    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the overview page of your
+    Set these environment variables with your own values:
+    1) AZURE_AI_PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the overview page of your
        Azure AI Foundry project.
-    2) MODEL_DEPLOYMENT_NAME - The AI model deployment name, to be used by your Agent, as found
+    2) AZURE_AI_MODEL_DEPLOYMENT_NAME - The AI model deployment name, to be used by your Agent, as found
        in your AI Foundry project.
 """
 
 import os
+from dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 
-endpoint = os.environ["PROJECT_ENDPOINT"]
-model_deployment_name = os.environ["MODEL_DEPLOYMENT_NAME"]
+load_dotenv()
+
+endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
+model_deployment_name = os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"]
 
 with DefaultAzureCredential(exclude_interactive_browser_credential=False) as credential:
 

sdk/ai/azure-ai-projects/samples/agents/sample_agents_async.py

@@ -15,24 +15,27 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity aiohttp
+    pip install azure-ai-projects azure-identity aiohttp python-dotenv
 
-    Set this environment variables with your own values:
-    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the overview page of your
+    Set these environment variables with your own values:
+    1) AZURE_AI_PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the overview page of your
        Azure AI Foundry project.
-    2) MODEL_DEPLOYMENT_NAME - The AI model deployment name, to be used by your Agent, as found
+    2) AZURE_AI_MODEL_DEPLOYMENT_NAME - The AI model deployment name, to be used by your Agent, as found
        in your AI Foundry project.
 """
 
 import os, asyncio
+from dotenv import load_dotenv
 from azure.identity.aio import DefaultAzureCredential
 from azure.ai.projects.aio import AIProjectClient
 
+load_dotenv()
+
 
 async def main() -> None:
 
-    endpoint = os.environ["PROJECT_ENDPOINT"]
-    model_deployment_name = os.environ["MODEL_DEPLOYMENT_NAME"]
+    endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
+    model_deployment_name = os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"]
 
     async with DefaultAzureCredential() as credential:
 

sdk/ai/azure-ai-projects/samples/connections/sample_connections.py

@@ -14,21 +14,24 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity
+    pip install azure-ai-projects azure-identity python-dotenv
 
     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
+    1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
        Azure AI Foundry project.
     2) CONNECTION_NAME - The name of a connection, as found in the "Connected resources" tab
        in the Management Center of your AI Foundry project.
 """
 
 import os
+from dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 from azure.ai.projects.models import ConnectionType
 
-endpoint = os.environ["PROJECT_ENDPOINT"]
+load_dotenv()
+
+endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
 connection_name = os.environ["CONNECTION_NAME"]
 
 with DefaultAzureCredential(exclude_interactive_browser_credential=False) as credential:

sdk/ai/azure-ai-projects/samples/connections/sample_connections_async.py

@@ -14,25 +14,28 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity aiohttp
+    pip install azure-ai-projects azure-identity aiohttp python-dotenv
 
     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
+    1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
        Azure AI Foundry project.
     2) CONNECTION_NAME - The name of a connection, as found in the "Connected resources" tab
        in the Management Center of your AI Foundry project.
 """
 
 import asyncio
 import os
+from dotenv import load_dotenv
 from azure.identity.aio import DefaultAzureCredential
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import ConnectionType
 
+load_dotenv()
+
 
 async def main() -> None:
 
-    endpoint = os.environ["PROJECT_ENDPOINT"]
+    endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
     connection_name = os.environ["CONNECTION_NAME"]
 
     async with DefaultAzureCredential() as credential:

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

@@ -15,10 +15,10 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity
+    pip install azure-ai-projects azure-identity python-dotenv
 
     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
+    1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
        Azure AI Foundry project.
     2) CONNECTION_NAME - Required. The name of the Azure Storage Account connection to use for uploading files.
     3) DATASET_NAME - Optional. The name of the Dataset to create and use in this sample.
@@ -29,11 +29,14 @@
 
 import os
 import re
+from dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 from azure.ai.projects.models import DatasetVersion
 
-endpoint = os.environ["PROJECT_ENDPOINT"]
+load_dotenv()
+
+endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
 connection_name = os.environ["CONNECTION_NAME"]
 dataset_name = os.environ.get("DATASET_NAME", "dataset-test")
 dataset_version_1 = os.environ.get("DATASET_VERSION_1", "1.0")

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

@@ -15,10 +15,10 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity aiohttp
+    pip install azure-ai-projects azure-identity aiohttp python-dotenv
 
     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
+    1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
        Azure AI Foundry project.
     2) CONNECTION_NAME - Required. The name of the Azure Storage Account connection to use for uploading files.
     3) DATASET_NAME - Optional. The name of the Dataset to create and use in this sample.
@@ -30,10 +30,13 @@
 import asyncio
 import os
 import re
+from dotenv import load_dotenv
 from azure.identity.aio import DefaultAzureCredential
 from azure.ai.projects.aio import AIProjectClient
 from azure.ai.projects.models import DatasetVersion
 
+load_dotenv()
+
 # Construct the paths to the data folder and data file used in this sample
 script_dir = os.path.dirname(os.path.abspath(__file__))
 data_folder = os.environ.get("DATA_FOLDER", os.path.join(script_dir, "data_folder"))
@@ -42,7 +45,7 @@
 
 async def main() -> None:
 
-    endpoint = os.environ["PROJECT_ENDPOINT"]
+    endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
     connection_name = os.environ["CONNECTION_NAME"]
     dataset_name = os.environ.get("DATASET_NAME", "dataset-test")
     dataset_version_1 = os.environ.get("DATASET_VERSION_1", "1.0")

sdk/ai/azure-ai-projects/samples/datasets/sample_datasets_download.py

@@ -16,10 +16,10 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity
+    pip install azure-ai-projects azure-identity python-dotenv
 
     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
+    1) AZURE_AI_PROJECT_ENDPOINT - Required. The Azure AI Project endpoint, as found in the overview page of your
        Azure AI Foundry project.
     2) CONNECTION_NAME - Required. The name of the Azure Storage Account connection to use for uploading files.
     3) DATASET_NAME - Optional. The name of the Dataset to create and use in this sample.
@@ -30,11 +30,14 @@
 
 import os
 import re
+from dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 from azure.storage.blob import ContainerClient
 
-endpoint = os.environ["PROJECT_ENDPOINT"]
+load_dotenv()
+
+endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
 connection_name = os.environ["CONNECTION_NAME"]
 dataset_name = os.environ.get("DATASET_NAME", "dataset-test")
 dataset_version = os.environ.get("DATASET_VERSION", "1.0")

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

@@ -13,23 +13,26 @@
 
     Before running the sample:
 
-    pip install azure-ai-projects azure-identity
+    pip install azure-ai-projects azure-identity python-dotenv
 
     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
+    1) AZURE_AI_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.
+    2) AZURE_AI_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 dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 from azure.ai.projects.models import ModelDeployment
 
-endpoint = os.environ["PROJECT_ENDPOINT"]
-model_deployment_name = os.environ["MODEL_DEPLOYMENT_NAME"]
+load_dotenv()
+
+endpoint = os.environ["AZURE_AI_PROJECT_ENDPOINT"]
+model_deployment_name = os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"]
 model_publisher = os.environ.get("MODEL_PUBLISHER", "Microsoft")
 model_name = os.environ.get("MODEL_NAME", "Phi-4")