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 grounding tool from
10    the Azure Agents service using a synchronous client.
11 
12USAGE:
13    python sample_agents_bing_grounding.py
14 
15    Before running the sample:
16 
17    pip install azure-ai-projects azure-ai-agents azure-identity
18 
19    Set these environment variables with your own values:
20    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
21                          page of your Azure AI Foundry portal.
22    2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
23       the "Models + endpoints" tab in your Azure AI Foundry project.
24    3) BING_CONNECTION_NAME - The name of a connection to the Bing resource as it is
25       listed in Azure AI Foundry connected resources.
26"""
27 
28import os
29from azure.ai.projects import AIProjectClient
30from azure.ai.agents.models import MessageRole, BingGroundingTool
31from azure.identity import DefaultAzureCredential
32 
33project_client = AIProjectClient(
34    endpoint=os.environ["PROJECT_ENDPOINT"],
35    credential=DefaultAzureCredential(),
36)
37 
38# [START create_agent_with_bing_grounding_tool]
39conn_id = project_client.connections.get(os.environ["BING_CONNECTION_NAME"]).id
40 
41# Initialize agent bing tool and add the connection id
42bing = BingGroundingTool(connection_id=conn_id)
43 
44# Create agent with the bing tool and process agent run
45with project_client:
46    agents_client = project_client.agents
47    agent = agents_client.create_agent(
48        model=os.environ["MODEL_DEPLOYMENT_NAME"],
49        name="my-agent",
50        instructions="You are a helpful agent",
51        tools=bing.definitions,
52    )
53    # [END create_agent_with_bing_grounding_tool]
54 
55    print(f"Created agent, ID: {agent.id}")
56 
57    # Create thread for communication
58    thread = agents_client.threads.create()
59    print(f"Created thread, ID: {thread.id}")
60 
61    # Create message to thread
62    message = agents_client.messages.create(
63        thread_id=thread.id,
64        role=MessageRole.USER,
65        content="How does wikipedia explain Euler's Identity?",
66    )
67    print(f"Created message, ID: {message.id}")
68 
69    # Create and process agent run in thread with tools
70    run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
71    print(f"Run finished with status: {run.status}")
72 
73    if run.status == "failed":
74        print(f"Run failed: {run.last_error}")
75 
76    # Fetch run steps to get the details of the agent run
77    run_steps = agents_client.run_steps.list(thread_id=thread.id, run_id=run.id)
78    for step in run_steps:
79        print(f"Step {step['id']} status: {step['status']}")
80        step_details = step.get("step_details", {})
81        tool_calls = step_details.get("tool_calls", [])
82 
83        if tool_calls:
84            print("  Tool calls:")
85            for call in tool_calls:
86                print(f"    Tool Call ID: {call.get('id')}")
87                print(f"    Type: {call.get('type')}")
88 
89                bing_grounding_details = call.get("bing_grounding", {})
90                if bing_grounding_details:
91                    print(f"    Bing Grounding ID: {bing_grounding_details.get('requesturl')}")
92 
93        print()  # add an extra newline between steps
94 
95    # Delete the agent when done
96    agents_client.delete_agent(agent.id)
97    print("Deleted agent")
98 
99    # Print the Agent's response message with optional citation
100    response_message = agents_client.messages.get_last_message_by_role(thread_id=thread.id, role=MessageRole.AGENT)
101    if response_message:
102        responses = []
103        for text_message in response_message.text_messages:
104            responses.append(text_message.text.value)
105        message = " ".join(responses)
106        for annotation in response_message.url_citation_annotations:
107            message = message.replace(
108                annotation.text, f" [{annotation.url_citation.title}]({annotation.url_citation.url})"
109            )
110        print(f"Agent response: {message}")