1# pylint: disable=line-too-long,useless-suppression
2# ------------------------------------
3# Copyright (c) Microsoft Corporation.
4# Licensed under the MIT License.
5# ------------------------------------
6from azure.ai.agents.models._models import RunStepConnectedAgentToolCall
7
8"""
9DESCRIPTION:
10 This sample demonstrates how to use Agent operations with the Connected Agent tool from
11 the Azure Agents service using a synchronous client.
12
13USAGE:
14 python sample_agents_multiple_connected_agents.py
15
16 Before running the sample:
17
18 pip install azure-ai-projects azure-ai-agents azure-identity
19
20 Set these environment variables with your own values:
21 1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
22 page of your Azure AI Foundry portal.
23 2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
24 the "Models + endpoints" tab in your Azure AI Foundry project.
25 3) STORAGE_QUEUE_URI - the storage service queue endpoint, triggering Azure function.
26
27 Please see Getting Started with Azure Functions page for more information on Azure Functions:
28 https://learn.microsoft.com/azure/azure-functions/functions-get-started
29 **Note:** The Azure Function may be only used in standard agent setup. Please follow the instruction on the web page
30 https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/infrastructure-setup/41-standard-agent-setup
31 to deploy an agent, capable of calling Azure Functions.
32"""
33
34import os
35from azure.ai.projects import AIProjectClient
36from azure.ai.agents.models import (
37 AzureFunctionStorageQueue,
38 AzureFunctionTool,
39 ConnectedAgentTool,
40 ListSortOrder,
41 MessageRole,
42 RunStepToolCallDetails,
43)
44from azure.identity import DefaultAzureCredential
45
46project_client = AIProjectClient(
47 endpoint=os.environ["PROJECT_ENDPOINT"],
48 credential=DefaultAzureCredential(),
49)
50storage_service_endpoint = os.environ["STORAGE_QUEUE_URI"]
51
52with project_client:
53 agents_client = project_client.agents
54
55 # [START create_two_toy_agents]
56 connected_agent_name = "stock_price_bot"
57 weather_agent_name = "weather_bot"
58
59 stock_price_agent = agents_client.create_agent(
60 model=os.environ["MODEL_DEPLOYMENT_NAME"],
61 name=connected_agent_name,
62 instructions=(
63 "Your job is to get the stock price of a company. If asked for the Microsoft stock price, always return $350."
64 ),
65 )
66
67 azure_function_tool = AzureFunctionTool(
68 name="GetWeather",
69 description="Get answers from the weather bot.",
70 parameters={
71 "type": "object",
72 "properties": {
73 "Location": {"type": "string", "description": "The location to get the weather for."},
74 },
75 },
76 input_queue=AzureFunctionStorageQueue(
77 queue_name="weather-input",
78 storage_service_endpoint=storage_service_endpoint,
79 ),
80 output_queue=AzureFunctionStorageQueue(
81 queue_name="weather-output",
82 storage_service_endpoint=storage_service_endpoint,
83 ),
84 )
85
86 weather_agent = agents_client.create_agent(
87 model=os.environ["MODEL_DEPLOYMENT_NAME"],
88 name=weather_agent_name,
89 instructions=(
90 "Your job is to get the weather for a given location. "
91 "Use the provided function to get the weather in the given location."
92 ),
93 tools=azure_function_tool.definitions,
94 )
95
96 # Initialize Connected Agent tools with the agent id, name, and description
97 connected_agent = ConnectedAgentTool(
98 id=stock_price_agent.id, name=connected_agent_name, description="Gets the stock price of a company"
99 )
100 connected_weather_agent = ConnectedAgentTool(
101 id=weather_agent.id, name=weather_agent_name, description="Gets the weather for a given location"
102 )
103 # [END create_two_toy_agents]
104
105 # [START create_agent_with_connected_agent_tool]
106 # Create agent with the Connected Agent tool and process assistant run
107 agent = agents_client.create_agent(
108 model=os.environ["MODEL_DEPLOYMENT_NAME"],
109 name="my-assistant",
110 instructions="You are a helpful assistant, and use the connected agents to get stock prices and weather.",
111 tools=[
112 connected_agent.definitions[0],
113 connected_weather_agent.definitions[0],
114 ],
115 )
116 # [END create_agent_with_connected_agent_tool]
117
118 print(f"Created agent, ID: {agent.id}")
119
120 # [START run_agent_with_connected_agent_tool]
121 # Create thread for communication
122 thread = agents_client.threads.create()
123 print(f"Created thread, ID: {thread.id}")
124
125 # Create message to thread
126 message = agents_client.messages.create(
127 thread_id=thread.id,
128 role=MessageRole.USER,
129 content="What is the stock price of Microsoft and the weather in Seattle?",
130 )
131 print(f"Created message, ID: {message.id}")
132
133 # Create and process Agent run in thread with tools
134 run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
135 print(f"Run finished with status: {run.status}")
136 # [END run_agent_with_connected_agent_tool]
137
138 if run.status == "failed":
139 print(f"Run failed: {run.last_error}")
140
141 # Delete the Agent when done
142 agents_client.delete_agent(agent.id)
143 print("Deleted agent")
144
145 # Delete the connected Agent when done
146 agents_client.delete_agent(stock_price_agent.id)
147 print("Deleted stock price agent")
148
149 # Delete the connected Agent when done
150 agents_client.delete_agent(weather_agent.id)
151 print("Deleted weather agent")
152
153 # [START list_tool_calls]
154 for run_step in agents_client.run_steps.list(thread_id=thread.id, run_id=run.id, order=ListSortOrder.ASCENDING):
155 if isinstance(run_step.step_details, RunStepToolCallDetails):
156 for tool_call in run_step.step_details.tool_calls:
157 if isinstance(tool_call, RunStepConnectedAgentToolCall):
158 print(
159 f"\tAgent: {tool_call.connected_agent.name} " f"query: {tool_call.connected_agent.arguments} ",
160 f"output: {tool_call.connected_agent.output}",
161 )
162 # [END list_tool_calls]
163
164 # [START list_messages]
165 # Fetch and log all messages
166 messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
167 for msg in messages:
168 if msg.text_messages:
169 last_text = msg.text_messages[-1]
170 text = last_text.text.value.replace("\u3010", "[").replace("\u3011", "]")
171 print(f"{msg.role}: {text}")
172 # [END list_messages]
173
174 agents_client.threads.delete(thread.id)
