1# ------------------------------------
2# Copyright (c) Microsoft Corporation.
3# Licensed under the MIT License.
4# ------------------------------------
5 
6"""
7DESCRIPTION:
8    This sample demonstrates how to use agent operations with toolset from
9    the Azure Agents service using a synchronous client.
10 
11USAGE:
12    python sample_agents_run_with_toolset.py
13 
14    Before running the sample:
15 
16    pip install azure-ai-projects azure-ai-agents azure-identity
17 
18    Set these environment variables with your own values:
19    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
20                          page of your Azure AI Foundry portal.
21    2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
22       the "Models + endpoints" tab in your Azure AI Foundry project.
23"""
24 
25import os, sys
26from azure.ai.projects import AIProjectClient
27from azure.identity import DefaultAzureCredential
28from azure.ai.agents.models import FunctionTool, ToolSet, CodeInterpreterTool
29 
30current_path = os.path.dirname(__file__)
31root_path = os.path.abspath(os.path.join(current_path, os.pardir, os.pardir))
32if root_path not in sys.path:
33    sys.path.insert(0, root_path)
34from samples.utils.user_functions import user_functions
35 
36project_client = AIProjectClient(
37    endpoint=os.environ["PROJECT_ENDPOINT"],
38    credential=DefaultAzureCredential(),
39)
40 
41# Create agent with toolset and process agent run
42with project_client:
43    agents_client = project_client.agents
44 
45    # Initialize agent toolset with user functions and code interpreter
46    # [START create_agent_toolset]
47    functions = FunctionTool(user_functions)
48    code_interpreter = CodeInterpreterTool()
49 
50    toolset = ToolSet()
51    toolset.add(functions)
52    toolset.add(code_interpreter)
53 
54    # To enable tool calls executed automatically
55    agents_client.enable_auto_function_calls(toolset)
56 
57    agent = agents_client.create_agent(
58        model=os.environ["MODEL_DEPLOYMENT_NAME"],
59        name="my-agent",
60        instructions="You are a helpful agent",
61        toolset=toolset,
62    )
63    # [END create_agent_toolset]
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="user",
74        content="Hello, send an email with the datetime and weather information in New York?",
75    )
76    print(f"Created message, ID: {message.id}")
77 
78    # Create and process agent run in thread with tools
79    # [START create_and_process_run]
80    run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
81    # [END create_and_process_run]
82    print(f"Run finished with status: {run.status}")
83 
84    if run.status == "failed":
85        print(f"Run failed: {run.last_error}")
86 
87    # Delete the agent when done
88    agents_client.delete_agent(agent.id)
89    print("Deleted agent")
90 
91    # Fetch and log all messages
92    messages = agents_client.messages.list(thread_id=thread.id)
93    for msg in messages:
94        if msg.text_messages:
95            last_text = msg.text_messages[-1]
96            print(f"{msg.role}: {last_text.text.value}")