Add samples for "responses" without using AIProjectClient

sdk/ai/azure-ai-projects/cspell.json

@@ -17,6 +17,7 @@
         "inpainting",
         "CSDL",
         "fstring",
+        "aiprojectclient",
     ],
     "ignorePaths": [
       "*.csv",

sdk/ai/azure-ai-projects/samples/responses/sample_responses_basic_without_aiprojectclient.py

@@ -0,0 +1,46 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+DESCRIPTION:
+    This sample demonstrates how to run a basic responses operation
+    using the synchronous OpenAI client. We do not use AIProjectClient
+    in this sample, but rather construct the OpenAI client directly.
+
+    See also https://platform.openai.com/docs/api-reference/responses/create?lang=python
+
+USAGE:
+    python sample_responses_basic_without_aiprojectclient.py
+
+    Before running the sample:
+
+    pip install openai azure-identity python-dotenv
+
+    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 portal.
+    2) AZURE_AI_MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
+       the "Models + endpoints" tab in your Azure AI Foundry project.
+"""
+
+import os
+from dotenv import load_dotenv
+from openai import OpenAI
+from azure.identity import DefaultAzureCredential, get_bearer_token_provider
+
+load_dotenv()
+
+openai = OpenAI(
+    api_key=get_bearer_token_provider(DefaultAzureCredential(), "https://ai.azure.com/.default"),
+    base_url=os.environ["AZURE_AI_PROJECT_ENDPOINT"].rstrip("/") + "/openai",
+    default_query={"api-version": "2025-11-15-preview"},
+)
+
+response = openai.responses.create(
+    model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+    input="How many feet are in a mile?",
+)
+
+print(f"Response output: {response.output_text}")

sdk/ai/azure-ai-projects/samples/responses/sample_responses_basic_without_aiprojectclient_async.py

@@ -0,0 +1,60 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+
+"""
+DESCRIPTION:
+    This sample demonstrates how to run a basic responses operation
+    using the asynchronous AsyncOpenAI client. We do not use AIProjectClient
+    in this sample, but rather construct the AsyncOpenAI client directly.
+
+    See also https://platform.openai.com/docs/api-reference/responses/create?lang=python
+
+USAGE:
+    python sample_responses_basic_without_aiprojectclient_async.py
+
+    Before running the sample:
+
+    pip install openai azure-identity python-dotenv
+
+    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 portal.
+    2) AZURE_AI_MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
+       the "Models + endpoints" tab in your Azure AI Foundry project.
+"""
+
+import asyncio
+import os
+from dotenv import load_dotenv
+from openai import AsyncOpenAI
+from azure.identity.aio import DefaultAzureCredential, get_bearer_token_provider
+
+load_dotenv()
+
+
+async def main() -> None:
+
+    credential = DefaultAzureCredential()
+
+    async with credential:
+
+        openai = AsyncOpenAI(
+            api_key=get_bearer_token_provider(credential, "https://ai.azure.com/.default"),
+            base_url=os.environ["AZURE_AI_PROJECT_ENDPOINT"].rstrip("/") + "/openai",
+            default_query={"api-version": "2025-11-15-preview"},
+        )
+
+        async with openai:
+
+            response = await openai.responses.create(
+                model=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
+                input="How many feet are in a mile?",
+            )
+
+            print(f"Response output: {response.output_text}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())