本文へ移動
cccskills
無料GitHub で公開

m365-agents-py

Microsoft 365 Agents SDK for Python. Build multichannel agents for Teams/M365/Copilot Studio with aiohttp hosting, AgentApplication routing, streaming responses, and MSAL-based auth. Triggers: "Microsoft 365 Agents SDK", "microsoft_agents", "AgentApplication", "start_agent_process", "TurnContext", "Copilot Studio client", "CloudAdapter".

インストール方法を見る

含まれるファイル(2)

  • SKILL.md13.5 KB
  • references/capabilities.md2.8 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Microsoft 365 Agents SDK (Python)

Build enterprise agents for Microsoft 365, Teams, and Copilot Studio using the Microsoft Agents SDK with aiohttp hosting, AgentApplication routing, streaming responses, and MSAL-based authentication.

Before implementation

  • Use the microsoft-docs MCP to verify the latest API signatures for AgentApplication, start_agent_process, and authentication options.
  • Confirm package versions on PyPI for the microsoft-agents-* packages you plan to use.

Important Notice - Import Changes

⚠️ Breaking Change: Recent updates have changed the Python import structure from microsoft.agents to microsoft_agents (using underscores instead of dots).

Installation

pip install microsoft-agents-hosting-core
pip install microsoft-agents-hosting-aiohttp
pip install microsoft-agents-activity
pip install microsoft-agents-authentication-msal
pip install microsoft-agents-copilotstudio-client
pip install python-dotenv aiohttp

Environment Variables (.env)

CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTID=<client-id>
CONNECTIONS__SERVICE_CONNECTION__SETTINGS__CLIENTSECRET=<client-secret>
CONNECTIONS__SERVICE_CONNECTION__SETTINGS__TENANTID=<tenant-id>

# Optional: OAuth handlers for auto sign-in
AGENTAPPLICATION__USERAUTHORIZATION__HANDLERS__GRAPH__SETTINGS__AZUREBOTOAUTHCONNECTIONNAME=<connection-name>

# Optional: Azure OpenAI for streaming (AAD auth via DefaultAzureCredential)
AZURE_OPENAI_ENDPOINT=<endpoint>
AZURE_OPENAI_API_VERSION=<version>

# Optional: Copilot Studio client
COPILOTSTUDIOAGENT__ENVIRONMENTID=<environment-id>
COPILOTSTUDIOAGENT__SCHEMANAME=<schema-name>
COPILOTSTUDIOAGENT__TENANTID=<tenant-id>
COPILOTSTUDIOAGENT__AGENTAPPID=<app-id>

Authentication & Lifecycle

🔑 Two rules apply to every code sample below:

  1. This SDK is async-first — use async def handlers and async with throughout.
  2. Use explicit auth managers and context-managed network resources. Use MsalConnectionManager for agent auth, and wrap per-request HTTP resources in async with (for example, aiohttp.ClientSession).

Snippets may abbreviate this setup, but production code should always follow both rules.

Core Workflow: aiohttp-hosted AgentApplication

import logging
from os import environ

from dotenv import load_dotenv
from aiohttp.web import Request, Response, Application, run_app

from microsoft_agents.activity import load_configuration_from_env
from microsoft_agents.hosting.core import (
    Authorization,
    AgentApplication,
    TurnState,
    TurnContext,
    MemoryStorage,
)
from microsoft_agents.hosting.aiohttp import (
    CloudAdapter,
    start_agent_process,
    jwt_authorization_middleware,
)
from microsoft_agents.authentication.msal import MsalConnectionManager

# Enable logging
ms_agents_logger = logging.getLogger("microsoft_agents")
ms_agents_logger.addHandler(logging.StreamHandler())
ms_agents_logger.setLevel(logging.INFO)

# Load configuration
load_dotenv()
agents_sdk_config = load_configuration_from_env(environ)

# Create storage and connection manager
STORAGE = MemoryStorage()
CONNECTION_MANAGER = MsalConnectionManager(**agents_sdk_config)
ADAPTER = CloudAdapter(connection_manager=CONNECTION_MANAGER)
AUTHORIZATION = Authorization(STORAGE, CONNECTION_MANAGER, **agents_sdk_config)

# Create AgentApplication
AGENT_APP = AgentApplication[TurnState](
    storage=STORAGE, adapter=ADAPTER, authorization=AUTHORIZATION, **agents_sdk_config
)


@AGENT_APP.conversation_update("membersAdded")
async def on_members_added(context: TurnContext, _state: TurnState):
    await context.send_activity("Welcome to the agent!")


@AGENT_APP.activity("message")
async def on_message(context: TurnContext, _state: TurnState):
    await context.send_activity(f"You said: {context.activity.text}")


@AGENT_APP.error
async def on_error(context: TurnContext, error: Exception):
    await context.send_activity("The agent encountered an error.")


# Server setup
async def entry_point(req: Request) -> Response:
    agent: AgentApplication = req.app["agent_app"]
    adapter: CloudAdapter = req.app["adapter"]
    return await start_agent_process(req, agent, adapter)


APP = Application(middlewares=[jwt_authorization_middleware])
APP.router.add_post("/api/messages", entry_point)
APP["agent_configuration"] = CONNECTION_MANAGER.get_default_connection_configuration()
APP["agent_app"] = AGENT_APP
APP["adapter"] = AGENT_APP.adapter

if __name__ == "__main__":
    run_app(APP, host="localhost", port=environ.get("PORT", 3978))

AgentApplication Routing

import re
from microsoft_agents.hosting.core import (
    AgentApplication, TurnState, TurnContext, MessageFactory
)
from microsoft_agents.activity import ActivityTypes

AGENT_APP = AgentApplication[TurnState](
    storage=STORAGE, adapter=ADAPTER, authorization=AUTHORIZATION, **agents_sdk_config
)

# Welcome handler
@AGENT_APP.conversation_update("membersAdded")
async def on_members_added(context: TurnContext, _state: TurnState):
    await context.send_activity("Welcome!")

# Regex-based message handler
@AGENT_APP.message(re.compile(r"^hello$", re.IGNORECASE))
async def on_hello(context: TurnContext, _state: TurnState):
    await context.send_activity("Hello!")

# Simple string message handler
@AGENT_APP.message("/status")
async def on_status(context: TurnContext, _state: TurnState):
    await context.send_activity("Status: OK")

# Auth-protected message handler
@AGENT_APP.message("/me", auth_handlers=["GRAPH"])
async def on_profile(context: TurnContext, state: TurnState):
    token_response = await AGENT_APP.auth.get_token(context, "GRAPH")
    if token_response and token_response.token:
        # Use token to call Graph API
        await context.send_activity("Profile retrieved")

# Invoke activity handler
@AGENT_APP.activity(ActivityTypes.invoke)
async def on_invoke(context: TurnContext, _state: TurnState):
    invoke_response = Activity(
        type=ActivityTypes.invoke_response, value={"status": 200}
    )
    await context.send_activity(invoke_response)

# Fallback message handler
@AGENT_APP.activity("message")
async def on_message(context: TurnContext, _state: TurnState):
    await context.send_activity(f"Echo: {context.activity.text}")

# Error handler
@AGENT_APP.error
async def on_error(context: TurnContext, error: Exception):
    await context.send_activity("An error occurred.")

Streaming Responses with Azure OpenAI

from openai import AsyncAzureOpenAI
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from microsoft_agents.activity import SensitivityUsageInfo

# AAD token provider (preferred over AZURE_OPENAI_API_KEY)
token_provider = get_bearer_token_provider(
    DefaultAzureCredential(),
    "https://cognitiveservices.azure.com/.default",
)

# Module-level singleton: client lives for the agent app lifetime.
CLIENT = AsyncAzureOpenAI(
    api_version=environ["AZURE_OPENAI_API_VERSION"],
    azure_endpoint=environ["AZURE_OPENAI_ENDPOINT"],
    azure_ad_token_provider=token_provider,
)

@AGENT_APP.message("poem")
async def on_poem_message(context: TurnContext, _state: TurnState):
    # Configure streaming response
    context.streaming_response.set_feedback_loop(True)
    context.streaming_response.set_generated_by_ai_label(True)
    context.streaming_response.set_sensitivity_label(
        SensitivityUsageInfo(
            type="https://schema.org/Message",
            schema_type="CreativeWork",
            name="Internal",
        )
    )
    context.streaming_response.queue_informative_update("Starting a poem...\n")

    # Stream from Azure OpenAI
    streamed_response = await CLIENT.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": "You are a creative assistant."},
            {"role": "user", "content": "Write a poem about Python."}
        ],
        stream=True,
    )

    try:
        async for chunk in streamed_response:
            if chunk.choices and chunk.choices[0].delta.content:
                context.streaming_response.queue_text_chunk(
                    chunk.choices[0].delta.content
                )
    finally:
        await context.streaming_response.end_stream()

OAuth / Auto Sign-In

@AGENT_APP.message("/logout")
async def logout(context: TurnContext, state: TurnState):
    await AGENT_APP.auth.sign_out(context, "GRAPH")
    await context.send_activity(MessageFactory.text("You have been logged out."))


@AGENT_APP.message("/me", auth_handlers=["GRAPH"])
async def profile_request(context: TurnContext, state: TurnState):
    user_token_response = await AGENT_APP.auth.get_token(context, "GRAPH")
    if user_token_response and user_token_response.token:
        # Use token to call Microsoft Graph
        async with aiohttp.ClientSession() as session:
            headers = {
                "Authorization": f"Bearer {user_token_response.token}",
                "Content-Type": "application/json",
            }
            async with session.get(
                "https://graph.microsoft.com/v1.0/me", headers=headers
            ) as response:
                if response.status == 200:
                    user_info = await response.json()
                    await context.send_activity(f"Hello, {user_info['displayName']}!")

Copilot Studio Client (Direct to Engine)

import asyncio
from msal import PublicClientApplication
from microsoft_agents.activity import ActivityTypes, load_configuration_from_env
from microsoft_agents.copilotstudio.client import (
    ConnectionSettings,
    CopilotClient,
)

# Token cache (local file for interactive flows)
class LocalTokenCache:
    # See samples for full implementation
    pass

def acquire_token(settings, app_client_id, tenant_id):
    pca = PublicClientApplication(
        client_id=app_client_id,
        authority=f"https://login.microsoftonline.com/{tenant_id}",
    )

    token_request = {"scopes": ["https://api.powerplatform.com/.default"]}
    accounts = pca.get_accounts()

    if accounts:
        response = pca.acquire_token_silent(token_request["scopes"], account=accounts[0])
        return response.get("access_token")
    else:
        response = pca.acquire_token_interactive(**token_request)
        return response.get("access_token")


async def main():
    settings = ConnectionSettings(
        environment_id=environ.get("COPILOTSTUDIOAGENT__ENVIRONMENTID"),
        agent_identifier=environ.get("COPILOTSTUDIOAGENT__SCHEMANAME"),
    )

    token = acquire_token(
        settings,
        app_client_id=environ.get("COPILOTSTUDIOAGENT__AGENTAPPID"),
        tenant_id=environ.get("COPILOTSTUDIOAGENT__TENANTID"),
    )

    # CopilotClient does not implement the context manager protocol.
    copilot_client = CopilotClient(settings, token)

    # Start conversation
    act = copilot_client.start_conversation(True)
    async for action in act:
        if action.text:
            print(action.text)

    # Ask question
    replies = copilot_client.ask_question("Hello!", action.conversation.id)
    async for reply in replies:
        if reply.type == ActivityTypes.message:
            print(reply.text)


asyncio.run(main())

Best Practices

  1. This SDK is async-first — use async def handlers and async with throughout.
  2. Always use context managers for clients and async credentials. Wrap every client in with Client(...) as client: (sync) or async with Client(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.
  3. Use microsoft_agents import prefix (underscores, not dots).
  4. Use MemoryStorage only for development; use BlobStorage or CosmosDB in production.
  5. Always use load_configuration_from_env(environ) to load SDK configuration.
  6. Include jwt_authorization_middleware in aiohttp Application middlewares.
  7. Use MsalConnectionManager for MSAL-based authentication.
  8. Call end_stream() in finally blocks when using streaming responses.
  9. Use auth_handlers parameter on message decorators for OAuth-protected routes.
  10. Keep secrets in environment variables, not in source code.

Reference Links

ResourceURL
Microsoft 365 Agents SDKhttps://learn.microsoft.com/en-us/microsoft-365/agents-sdk/
GitHub samples (Python)https://github.com/microsoft/Agents-for-python
PyPI packageshttps://pypi.org/search/?q=microsoft-agents
Integrate with Copilot Studiohttps://learn.microsoft.com/en-us/microsoft-365/agents-sdk/integrate-with-mcs

Reference Files

FileContents
references/capabilities.mdAdditional non-hero capabilities, operation-group coverage, and production checklists.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or implementing streaming responses. Covers function tools, structured outputs, and multi-tool agents.

日本語の概要は準備中です。原文の説明を表示しています。

microsoft/skills3,1012026年10月10日 更新

Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway", "onboard AKS cluster", "install AI Runway", "airunway setup", "deploy model to AKS", "GPU inference on AKS", "KAITO setup on AKS", "run LLM on AKS", "vLLM on AKS", "set up model serving on AKS", "AI Runway controller".

日本語の概要は準備中です。原文の説明を表示しています。

microsoft/skills3,1012026年10月10日 更新

Diagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. WHEN: 'Insufficient nvidia.com/gpu', GPU pod Pending, model-load OOM, DCGM/VRAM, KAITO Workspace not ready, or GPU autoscaling. DO NOT USE FOR: setup (airunway-aks-setup), non-GPU incidents (aks-troubleshooting), standalone VM quota (azure-quotas), or generic cost (cost-analysis or cost-optimization from the optional azure-cost plugin).

日本語の概要は準備中です。原文の説明を表示しています。

microsoft/skills3,1012026年10月10日 更新

Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.

日本語の概要は準備中です。原文の説明を表示しています。

microsoft/skills3,1012026年10月10日 更新

Collects bounded packet captures from AKS nodes and Azure network configuration for wire-level evidence. WHEN: "capture packets on an AKS node", "take a pcap", "run tcpdump on AKS", "prove where packets drop". Use for explicit packet-capture intent after read-only diagnostics, not general AKS connectivity or ingress troubleshooting.

日本語の概要は準備中です。原文の説明を表示しています。

microsoft/skills3,1012026年10月10日 更新

Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. WHEN: pod crashes or Pending, CrashLoopBackOff, OOMKilled, ImagePullBackOff, node NotReady, DNS or ingress failure, connectivity timeout, network policy, SNAT exhaustion, node-pool scaling blocked by QuotaExceeded or InsufficientVCPUQuota, upgrade stuck, spot or zone disruption, a bare VMExtensionProvisioningError or AllocationFailed wrapper, an uncataloged capacity symptom, or 'investigate my AKS cluster'. DO NOT USE FOR: packet capture (use aks-network-capture); GPU or model-serving issues (use aks-gpu-inference); cluster creation or provisioning (use azure-kubernetes); cost (use cost-analysis from the optional azure-cost plugin); pod rightsizing (use azure-kubernetes); a fully qualified documented AKS signature with every required nested qualifier (use aks-known-issues); standalone failures on non-AKS Azure resources (use azure-diagnostics). Unqualified errors and open-ended incidents stay here only for AKS.

日本語の概要は準備中です。原文の説明を表示しています。

microsoft/skills3,1012026年10月10日 更新

microsoft のスキルをすべて見る

このスキルの問題を報告する