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 Connected Agent tool from
10    the Azure Agents service using a synchronous client.
11 
12USAGE:
13    python sample_agents_connected_agent.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"""
25 
26import os
27from azure.ai.projects import AIProjectClient
28from azure.ai.agents.models import ConnectedAgentTool, MessageRole
29from azure.identity import DefaultAzureCredential
30 
31project_client = AIProjectClient(
32    endpoint=os.environ["PROJECT_ENDPOINT"],
33    credential=DefaultAzureCredential(),
34)
35 
36connected_agent_name = "stock_price_bot"
37 
38with project_client:
39    agents_client = project_client.agents
40 
41    stock_price_agent = agents_client.create_agent(
42        model=os.environ["MODEL_DEPLOYMENT_NAME"],
43        name=connected_agent_name,
44        instructions=(
45            "Your job is to get the stock price of a company. If asked for the Microsoft stock price, always return $350."
46        ),
47    )
48 
49    # [START create_agent_with_connected_agent_tool]
50    # Initialize Connected Agent tool with the agent id, name, and description
51    connected_agent = ConnectedAgentTool(
52        id=stock_price_agent.id, name=connected_agent_name, description="Gets the stock price of a company"
53    )
54 
55    # Create agent with the Connected Agent tool and process assistant run
56    agent = agents_client.create_agent(
57        model=os.environ["MODEL_DEPLOYMENT_NAME"],
58        name="my-assistant",
59        instructions="You are a helpful assistant, and use the connected agents to get stock prices.",
60        tools=connected_agent.definitions,
61    )
62    # [END create_agent_with_connected_agent_tool]
63 
64    print(f"Created agent, ID: {agent.id}")
65 
66    # Create thread for communication
67    thread = agents_client.threads.create()
68    print(f"Created thread, ID: {thread.id}")
69 
70    # Create message to thread
71    message = agents_client.messages.create(
72        thread_id=thread.id,
73        role=MessageRole.USER,
74        content="What is the stock price of Microsoft?",
75    )
76    print(f"Created message, ID: {message.id}")
77 
78    # Create and process Agent run in thread with tools
79    run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
80    print(f"Run finished with status: {run.status}")
81 
82    if run.status == "failed":
83        print(f"Run failed: {run.last_error}")
84 
85    # Delete the Agent when done
86    agents_client.delete_agent(agent.id)
87    print("Deleted agent")
88 
89    # Delete the connected Agent when done
90    agents_client.delete_agent(stock_price_agent.id)
91    print("Deleted stock price agent")
92 
93    # Fetch and log all messages
94    messages = agents_client.messages.list(thread_id=thread.id)
95    for msg in messages:
96        if msg.text_messages:
97            last_text = msg.text_messages[-1]
98            print(f"{msg.role}: {last_text.text.value}")