Unable to connect the agent with AI Search Tool

- **Package Name**: Azure ai
- **Package Version**: Latest
- **Operating System**: Windows 11
- **Python Version**: 3.13

**Describe the bug**
Tried to connect the agent with the ai search tool using the template present in the github. But getting the following error:
Run failed: {'code': 'tool_user_error', 'message': 'Error: search_service_request_error; Unable to connect to Azure AI Search Resource. Please ensure the Azure AI Search Connection has the correct endpoint and the search resouce has appropriate network settings for the agents setup. Cannot connect to host azureaiservice.search.windows.net:443 ssl:default [DNS server returned answer with no data]'}

**To Reproduce**
Steps to reproduce the behavior:
code:

# pylint: disable=line-too-long,useless-suppression
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------

"""
DESCRIPTION:
This sample demonstrates how to use agent operations with the
Azure AI Search tool from the Azure agents service using a synchronous client.

PREREQUISITES:
You will need an Azure AI Search Resource.
If you already have one, you must create an agent that can use an existing Azure AI Search index:
https://learn.microsoft.com/azure/ai-services/agents/how-to/tools/azure-ai-search?tabs=azurecli%2Cpython&pivots=overview-azure-ai-search

If you do not already have an agent Setup with an Azure AI Search resource, follow the guide for a Standard agent setup:
https://learn.microsoft.com/azure/ai-services/agents/quickstart?pivots=programming-language-python-azure

USAGE:
python sample_agents_azure_ai_search.py

Before running the sample:

pip install azure-ai-projects azure-ai-projects azure-identity

Set these environment variables with your own values:
1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
page of your Azure AI Foundry portal.
2) 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.
3) AI_SEARCH_CONNECTION_NAME - The connection name of the AI Search connection to your Foundry project,
as found under the "Name" column in the "Connected Resources" tab in your Azure AI Foundry project.
"""

import os
from azure.ai.projects import AIProjectClient
from azure.ai.projects.models import ConnectionType
from azure.identity import DefaultAzureCredential
from azure.ai.agents.models import AzureAISearchQueryType, AzureAISearchTool, ListSortOrder, MessageRole, AgentsNamedToolChoice

with AIProjectClient(
endpoint=os.environ["PROJECT_ENDPOINT"],
credential=DefaultAzureCredential(),
) as project_client:

# [START create_agent_with_azure_ai_search_tool]
conn_id = project_client.connections.get_default(ConnectionType.AZURE_AI_SEARCH).id

print(conn_id)

# Initialize agent AI search tool and add the search index connection id
ai_search = AzureAISearchTool(
index_connection_id=conn_id,
index_name="sample-index",
query_type=AzureAISearchQueryType.SIMPLE,
top_k=3,
filter="",
)

# Create agent with AI search tool and process agent run
agents_client = project_client.agents

agent = agents_client.create_agent(
model=os.environ["MODEL_DEPLOYMENT_NAME"],
name="my-agent",
instructions="You are a helpful agent. Always make call to AI Search Tool to answer the user.",
tools=ai_search.definitions,
tool_resources=ai_search.resources,
)
# [END create_agent_with_azure_ai_search_tool]
print(f"Created agent, ID: {agent.id}")

# Create thread for communication
thread = agents_client.threads.create()
print(f"Created thread, ID: {thread.id}")

# Create message to thread
message = agents_client.messages.create(
thread_id=thread.id,
role="user",
content="What features does Premium include? Use the ai search tool to answer this question",
)
print(f"Created message, ID: {message.id}")

# Create and process agent run in thread with tools
run = agents_client.runs.create_and_process(
thread_id=thread.id,
agent_id=agent.id
# tool_choice=AgentsNamedToolChoice(type="azure_ai_search")
)
print(f"Run finished with status: {run.status}")

if run.status == "failed":
print(f"Run failed: {run.last_error}")

# Fetch run steps to get the details of the agent run
run_steps = agents_client.run_steps.list(thread_id=thread.id, run_id=run.id)
for step in run_steps:
print(f"Step {step['id']} status: {step['status']}")
step_details = step.get("step_details", {})
print(f" Tool choice: {step_details}")
tool_calls = step_details.get("tool_calls", [])
# print(f" Tool calls : {tool_calls}")

if tool_calls:
print(" Tool calls:")
for call in tool_calls:
print(f" Tool Call ID: {call.get('id')}")
print(f" Type: {call.get('type')}")

azure_ai_search_details = call.get("azure_ai_search", {})
if azure_ai_search_details:
print(f" azure_ai_search input: {azure_ai_search_details.get('input')}")
print(f" azure_ai_search output: {azure_ai_search_details.get('output')}")
print() # add an extra newline between steps

# Delete the agent when done
agents_client.delete_agent(agent.id)
print("Deleted agent")

# [START populate_references_agent_with_azure_ai_search_tool]
# Fetch and log all messages
messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
for message in messages:
if message.role == MessageRole.AGENT and message.url_citation_annotations:
placeholder_annotations = {
annotation.text: f" [see {annotation.url_citation.title}] ({annotation.url_citation.url})"
for annotation in message.url_citation_annotations
}
for message_text in message.text_messages:
message_str = message_text.text.value
for k, v in placeholder_annotations.items():
message_str = message_str.replace(k, v)
print(f"{message.role}: {message_str}")
else:
for message_text in message.text_messages:
print(f"{message.role}: {message_text.text.value}")
# [END populate_references_agent_with_azure_ai_search_tool]
**Expected behavior**
Expected it to give result by searching the ai search tool bar.

**Screenshots**
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**Additional context**
Add any other context about the problem here.