Python: AzureAI Agent AI Search Sample (#1281)

* azure ai search sample

* small fix

python/packages/azure-ai/agent_framework_azure_ai/_chat_client.py

@@ -907,6 +907,10 @@ class AzureAIAgentClient(BaseChatClient):
                                 filter=additional_props.get("filter", ""),
                             )
                             tool_definitions.extend(ai_search.definitions)
+                            # Add tool resources for Azure AI Search
+                            if run_options is not None:
+                                run_options.setdefault("tool_resources", {})
+                                run_options["tool_resources"].update(ai_search.resources)
                 case ToolDefinition():
                     tool_definitions.append(tool)
                 case dict():

python/samples/getting_started/agents/azure_ai/README.md

@@ -12,6 +12,7 @@ This folder contains examples demonstrating different ways to create and use age
 | [`azure_ai_with_existing_agent.py`](azure_ai_with_existing_agent.py) | Shows how to work with a pre-existing agent by providing the agent ID to the Azure AI chat client. This example also demonstrates proper cleanup of manually created agents. |
 | [`azure_ai_with_existing_thread.py`](azure_ai_with_existing_thread.py) | Shows how to work with a pre-existing thread by providing the thread ID to the Azure AI chat client. This example also demonstrates proper cleanup of manually created threads. |
 | [`azure_ai_with_explicit_settings.py`](azure_ai_with_explicit_settings.py) | Shows how to create an agent with explicitly configured `AzureAIAgentClient` settings, including project endpoint, model deployment, credentials, and agent name. |
+| [`azure_ai_with_azure_ai_search.py`](azure_ai_with_azure_ai_search.py) | Demonstrates how to use Azure AI Search with Azure AI agents to search through indexed data. Shows how to configure search parameters, query types, and integrate with existing search indexes. |
 | [`azure_ai_with_file_search.py`](azure_ai_with_file_search.py) | Demonstrates how to use the HostedFileSearchTool with Azure AI agents to search through uploaded documents. Shows file upload, vector store creation, and querying document content. Includes both streaming and non-streaming examples. |
 | [`azure_ai_with_function_tools.py`](azure_ai_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_ai_with_hosted_mcp.py`](azure_ai_with_hosted_mcp.py) | Shows how to integrate Azure AI agents with hosted Model Context Protocol (MCP) servers for enhanced functionality and tool integration. Demonstrates remote MCP server connections and tool discovery. |

python/samples/getting_started/agents/azure_ai/azure_ai_with_azure_ai_search.py

@@ -0,0 +1,73 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+
+from agent_framework import ChatAgent, HostedFileSearchTool
+from agent_framework.azure import AzureAIAgentClient
+from azure.identity.aio import AzureCliCredential
+
+"""
+Azure AI Agent with Azure AI Search Example
+
+This sample demonstrates how to create an Azure AI agent that uses Azure AI Search
+to search through indexed hotel data and answer user questions about hotels.
+
+Prerequisites:
+1. Set AZURE_AI_PROJECT_ENDPOINT and AZURE_AI_MODEL_DEPLOYMENT_NAME environment variables
+2. Ensure you have an Azure AI Search connection configured in your Azure AI project
+3. The search index "hotels-sample-index" should exist in your Azure AI Search service
+   (you can create this using the Azure portal with sample hotel data)
+
+Environment variables:
+- AZURE_AI_PROJECT_ENDPOINT: Your Azure AI project endpoint
+- AZURE_AI_MODEL_DEPLOYMENT_NAME: The name of your model deployment
+"""
+
+# Test queries to verify Azure AI Search is working with the hotels-sample-index
+USER_INPUTS = [
+    "Search the hotel database for Stay-Kay City Hotel and give me detailed information.",
+]
+
+
+async def main() -> None:
+    """Main function demonstrating Azure AI agent with Azure AI Search capabilities."""
+
+    # 1. Create Azure AI Search tool using HostedFileSearchTool
+    # The tool will automatically use the default Azure AI Search connection from your project
+    azure_ai_search_tool = HostedFileSearchTool(
+        additional_properties={
+            "index_name": "hotels-sample-index",  # Name of your search index
+            "query_type": "simple",  # Use simple search
+            "top_k": 10,  # Get more comprehensive results
+        },
+    )
+
+    # 2. Use AzureAIAgentClient as async context manager for automatic cleanup
+    async with (
+        AzureAIAgentClient(async_credential=AzureCliCredential()) as client,
+        ChatAgent(
+            chat_client=client,
+            name="HotelSearchAgent",
+            instructions=("You are a helpful travel assistant that searches hotel information."),
+            tools=azure_ai_search_tool,
+        ) as agent,
+    ):
+        print("=== Azure AI Agent with Azure AI Search ===")
+        print("This agent can search through hotel data to help you find accommodations.\n")
+
+        # 3. Simulate conversation with the agent
+        for user_input in USER_INPUTS:
+            print(f"User: {user_input}")
+            print("Agent: ", end="", flush=True)
+
+            # Stream the response for better user experience
+            async for chunk in agent.run_stream(user_input):
+                if chunk.text:
+                    print(chunk.text, end="", flush=True)
+            print("\n" + "=" * 50 + "\n")
+
+        print("Hotel search conversation completed!")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())