File: sample_agents_basics_async.py

package info (click to toggle)
python-azure 20250829%2Bgit-3
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid
  • size: 756,824 kB
  • sloc: python: 6,224,989; ansic: 804; javascript: 287; makefile: 198; sh: 195; xml: 109
file content (82 lines) | stat: -rw-r--r-- 2,831 bytes parent folder | download
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
# pylint: disable=line-too-long,useless-suppression
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------

"""
DESCRIPTION:
    This sample demonstrates how to use basic agent operations from
    the Azure Agents service using a asynchronous client.

USAGE:
    python sample_agents_basics_async.py

    Before running the sample:

    pip install azure-ai-projects azure-ai-agents azure-identity aiohttp

    Set these environment variables with your own values:
    1) PROJECT_ENDPOINT - The Azure AI Project endpoint, as found in the Overview
                          page of your Azure AI Foundry portal.
    2) MODEL_DEPLOYMENT_NAME - The deployment name of the AI model, as found under the "Name" column in
       the "Models + endpoints" tab in your Azure AI Foundry project.
"""
import asyncio
import time

from azure.ai.projects.aio import AIProjectClient
from azure.ai.agents.models import MessageTextContent, ListSortOrder
from azure.identity.aio import DefaultAzureCredential

import os


async def main() -> None:

    project_client = AIProjectClient(
        endpoint=os.environ["PROJECT_ENDPOINT"],
        credential=DefaultAzureCredential(),
    )

    async with project_client:
        agents_client = project_client.agents

        agent = await agents_client.create_agent(
            model=os.environ["MODEL_DEPLOYMENT_NAME"], name="my-agent", instructions="You are helpful agent"
        )
        print(f"Created agent, agent ID: {agent.id}")

        thread = await agents_client.threads.create()
        print(f"Created thread, thread ID: {thread.id}")

        message = await agents_client.messages.create(thread_id=thread.id, role="user", content="Hello, tell me a joke")
        print(f"Created message, message ID: {message.id}")

        run = await agents_client.runs.create(thread_id=thread.id, agent_id=agent.id)

        # Poll the run as long as run status is queued or in progress
        while run.status in ["queued", "in_progress", "requires_action"]:
            # Wait for a second
            time.sleep(1)
            run = await agents_client.runs.get(thread_id=thread.id, run_id=run.id)
            print(f"Run status: {run.status}")

        if run.status == "failed":
            print(f"Run error: {run.last_error}")

        await agents_client.delete_agent(agent.id)
        print("Deleted agent")

        messages = agents_client.messages.list(
            thread_id=thread.id,
            order=ListSortOrder.ASCENDING,
        )
        async for msg in messages:
            last_part = msg.content[-1]
            if isinstance(last_part, MessageTextContent):
                print(f"{msg.role}: {last_part.text.value}")


if __name__ == "__main__":
    asyncio.run(main())