1# pylint: disable=line-too-long,useless-suppression
2# ------------------------------------
3# Copyright (c) Microsoft Corporation.
4# Licensed under the MIT License.
5# ------------------------------------
6 
7"""
8DESCRIPTION:
9    This sample demonstrates how to use Agent operations with the Bing Custom Search tool from
10    the Azure Agents service using a synchronous client.
11    For more information on the Bing Custom Search tool, see: https://aka.ms/AgentCustomSearchDoc
12 
13USAGE:
14    python sample_agents_bing_custom_search.py
15 
16    Before running the sample:
17 
18    pip install azure-identity
19    pip install --pre azure-ai-projects
20 
21    Set this environment variables with your own values:
22    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
23                          page of your Azure AI Foundry portal.
24    2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
25       the "Models + endpoints" tab in your Azure AI Foundry project.
26    3) BING_CUSTOM_CONNECTION_NAME - The name of a connection to the custom search Bing resource as it is
27       listed in Azure AI Foundry connected resources.
28    4) BING_CONFIGURATION_NAME - the name of a search configuration in Grounding with Bing Custom Search
29       resource.
30"""
31 
32import os
33from azure.ai.projects import AIProjectClient
34from azure.identity import DefaultAzureCredential
35from azure.ai.agents.models import BingCustomSearchTool, ListSortOrder
36 
37project_client = AIProjectClient(
38    endpoint=os.environ["PROJECT_ENDPOINT"],
39    credential=DefaultAzureCredential(),
40)
41 
42conn_id = project_client.connections.get(os.environ["BING_CUSTOM_CONNECTION_NAME"]).id
43 
44# Initialize Bing Custom Search tool with connection id and instance name
45bing_custom_tool = BingCustomSearchTool(connection_id=conn_id, instance_name=os.environ["BING_CONFIGURATION_NAME"])
46 
47# Create Agent with the Bing Custom Search tool and process Agent run
48with project_client:
49    agents_client = project_client.agents
50 
51    agent = agents_client.create_agent(
52        model=os.environ["MODEL_DEPLOYMENT_NAME"],
53        name="my-agent",
54        instructions="You are a helpful agent",
55        tools=bing_custom_tool.definitions,
56    )
57    print(f"Created agent, ID: {agent.id}")
58 
59    # Create thread for communication
60    thread = agents_client.threads.create()
61    print(f"Created thread, ID: {thread.id}")
62 
63    # Create message to thread
64    message = agents_client.messages.create(
65        thread_id=thread.id,
66        role="user",
67        content="How many medals did the USA win in the 2024 summer olympics?",
68    )
69    print(f"Created message, ID: {message.id}")
70 
71    # Create and process Agent run in thread with tools
72    run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
73    print(f"Run finished with status: {run.status}")
74 
75    if run.status == "failed":
76        print(f"Run failed: {run.last_error}")
77 
78    # Delete the Agent when done
79    agents_client.delete_agent(agent.id)
80    print("Deleted agent")
81 
82    # Fetch and log all messages
83    messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
84    for msg in messages:
85        if msg.text_messages:
86            responses = []
87            for text_message in msg.text_messages:
88                responses.append(text_message.text.value)
89            message = " ".join(responses)
90            for annotation in msg.url_citation_annotations:
91                message = message.replace(
92                    annotation.text, f" [{annotation.url_citation.title}]({annotation.url_citation.url})"
93                )
94            print(f"{msg.role}: {message}")