diff --git a/python/packages/core/tests/azure/test_azure_responses_client.py b/python/packages/core/tests/azure/test_azure_responses_client.py
index a495d05837..9b59a3d41a 100644
--- a/python/packages/core/tests/azure/test_azure_responses_client.py
+++ b/python/packages/core/tests/azure/test_azure_responses_client.py
@@ -578,7 +578,6 @@ async def test_azure_responses_client_agent_hosted_mcp_tool() -> None:
 
 @pytest.mark.flaky
 @skip_if_azure_integration_tests_disabled
-@pytest.mark.skip(reason="File search requires API key auth, subscription only allows token auth")
 async def test_azure_responses_client_file_search() -> None:
     """Test Azure responses client with file search tool."""
     azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
@@ -586,7 +585,7 @@ async def test_azure_responses_client_file_search() -> None:
     assert isinstance(azure_responses_client, ChatClientProtocol)
 
     file_id, vector_store = await create_vector_store(azure_responses_client)
-    # Test that the client will use the web search tool
+    # Test that the client will use the file search tool
     response = await azure_responses_client.get_response(
         messages=[
             ChatMessage(
@@ -605,7 +604,6 @@ async def test_azure_responses_client_file_search() -> None:
 
 @pytest.mark.flaky
 @skip_if_azure_integration_tests_disabled
-@pytest.mark.skip(reason="File search requires API key auth, subscription only allows token auth")
 async def test_azure_responses_client_file_search_streaming() -> None:
     """Test Azure responses client with file search tool and streaming."""
     azure_responses_client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
@@ -613,7 +611,7 @@ async def test_azure_responses_client_file_search_streaming() -> None:
     assert isinstance(azure_responses_client, ChatClientProtocol)
 
     file_id, vector_store = await create_vector_store(azure_responses_client)
-    # Test that the client will use the web search tool
+    # Test that the client will use the file search tool
     response = azure_responses_client.get_streaming_response(
         messages=[
             ChatMessage(
diff --git a/python/samples/getting_started/agents/azure_openai/README.md b/python/samples/getting_started/agents/azure_openai/README.md
index a5b1db617c..466860de3e 100644
--- a/python/samples/getting_started/agents/azure_openai/README.md
+++ b/python/samples/getting_started/agents/azure_openai/README.md
@@ -21,6 +21,7 @@ This folder contains examples demonstrating different ways to create and use age
 | [`azure_responses_client_image_analysis.py`](azure_responses_client_image_analysis.py) | Shows how to use Azure OpenAI Responses for image analysis and vision tasks. Demonstrates multi-modal messages combining text and image content using remote URLs. |
 | [`azure_responses_client_with_code_interpreter.py`](azure_responses_client_with_code_interpreter.py) | Shows how to use the HostedCodeInterpreterTool with Azure agents to write and execute Python code. Includes helper methods for accessing code interpreter data from response chunks. |
 | [`azure_responses_client_with_explicit_settings.py`](azure_responses_client_with_explicit_settings.py) | Shows how to initialize an agent with a specific responses client, configuring settings explicitly including endpoint and deployment name. |
+| [`azure_responses_client_with_file_search.py`](azure_responses_client_with_file_search.py) | Demonstrates using HostedFileSearchTool with Azure OpenAI Responses Client for direct document-based question answering and information retrieval from vector stores. |
 | [`azure_responses_client_with_function_tools.py`](azure_responses_client_with_function_tools.py) | Demonstrates how to use function tools with agents. Shows both agent-level tools (defined when creating the agent) and query-level tools (provided with specific queries). |
 | [`azure_responses_client_with_local_mcp.py`](azure_responses_client_with_local_mcp.py) | Shows how to integrate Azure OpenAI Responses Client with local Model Context Protocol (MCP) servers using MCPStreamableHTTPTool for extended functionality. |
 | [`azure_responses_client_with_thread.py`](azure_responses_client_with_thread.py) | Demonstrates thread management with Azure agents, including automatic thread creation for stateless conversations and explicit thread management for maintaining conversation context across multiple interactions. |
diff --git a/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_file_search.py b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_file_search.py
new file mode 100644
index 0000000000..b42c7acf2f
--- /dev/null
+++ b/python/samples/getting_started/agents/azure_openai/azure_responses_client_with_file_search.py
@@ -0,0 +1,71 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import ChatAgent, HostedFileSearchTool, HostedVectorStoreContent
+from agent_framework.azure import AzureOpenAIResponsesClient
+from azure.identity import AzureCliCredential
+
+"""
+Azure OpenAI Responses Client with File Search Example
+
+This sample demonstrates using HostedFileSearchTool with Azure OpenAI Responses Client
+for direct document-based question answering and information retrieval.
+
+Prerequisites:
+- Set environment variables:
+  - AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpoint URL
+  - AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME: Your Responses API deployment name
+- Authenticate via 'az login' for AzureCliCredential
+"""
+
+# Helper functions
+
+
+async def create_vector_store(client: AzureOpenAIResponsesClient) -> tuple[str, HostedVectorStoreContent]:
+    """Create a vector store with sample documents."""
+    file = await client.client.files.create(
+        file=("todays_weather.txt", b"The weather today is sunny with a high of 75F."), purpose="assistants"
+    )
+    vector_store = await client.client.vector_stores.create(
+        name="knowledge_base",
+        expires_after={"anchor": "last_active_at", "days": 1},
+    )
+    result = await client.client.vector_stores.files.create_and_poll(vector_store_id=vector_store.id, file_id=file.id)
+    if result.last_error is not None:
+        raise Exception(f"Vector store file processing failed with status: {result.last_error.message}")
+
+    return file.id, HostedVectorStoreContent(vector_store_id=vector_store.id)
+
+
+async def delete_vector_store(client: AzureOpenAIResponsesClient, file_id: str, vector_store_id: str) -> None:
+    """Delete the vector store after using it."""
+    await client.client.vector_stores.delete(vector_store_id=vector_store_id)
+    await client.client.files.delete(file_id=file_id)
+
+
+async def main() -> None:
+    print("=== Azure OpenAI Responses Client with File Search Example ===\n")
+
+    # Initialize Responses client
+    # Make sure you're logged in via 'az login' before running this sample
+    client = AzureOpenAIResponsesClient(credential=AzureCliCredential())
+
+    file_id, vector_store = await create_vector_store(client)
+
+    agent = ChatAgent(
+        chat_client=client,
+        instructions="You are a helpful assistant that can search through files to find information.",
+        tools=[HostedFileSearchTool(inputs=vector_store)],
+    )
+
+    query = "What is the weather today? Do a file search to find the answer."
+    print(f"User: {query}")
+    result = await agent.run(query)
+    print(f"Agent: {result}\n")
+
+    await delete_vector_store(client, file_id, vector_store.vector_store_id)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())