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agent-framework/python/packages/copilotstudio
T
Evan Mattson f5419b9f38 Python: bump package versions for 1.2.2 release (#5561)
* Python: bump package versions for 1.2.2 release

PATCH bump (1.2.1 -> 1.2.2) for the released cohort. Five PRs land in this
window:

- agent-framework-openai: fix file_search citations breaking the assistant-
  message history roundtrip (#5557) โ€” drives the released-tier PATCH
- agent-framework-orchestrations: [BREAKING] standardize orchestration
  terminal outputs as AgentResponse (#5301)
- agent-framework-core, agent-framework-declarative: preserve Workflow.run()
  shared state across calls, accept list[Message] in declarative start
  executor, and coerce Enum values when serializing PowerFx symbols (#5531)
- agent-framework-foundry-hosting: add hosted Durable Workflow support
  (#5531)
- agent-framework-azure-contentunderstanding: new alpha package โ€” Azure AI
  Content Understanding context provider (#4829)
- dependencies: workspace package dependency refresh (#5555)

Per lockstep convention, all 21 beta packages stamp 1.0.0b260429 and all 4
alpha packages (now including the new contentunderstanding) stamp
1.0.0a260429. Date stamp reflects 2026-04-29 Pacific. Every non-core package
floor on agent-framework-core is raised to >=1.2.2; the new
contentunderstanding package's stale >=1.0.0 floor is brought into line.

Two follow-on fixes bundled to keep validate-dependency-bounds-test green
at lowest-direct resolution:
- Bump agent-framework-azure-contentunderstanding's azure-ai-content
  understanding lower bound from >=1.0.0 to >=1.0.1 (1.0.0 ships without
  proper typing โ€” pyright reports 65 unknown-type errors)
- Add pyright ignore comments to core/foundry/__init__.pyi for the new
  alpha package's type-stub imports, since alpha packages are not in
  core's [all] extra and therefore aren't installed at lowest-direct

* Python: add #5552 to 1.2.2 CHANGELOG

Add the streaming-span observability fix to the Fixed section. PR is on
upstream/main but not yet pulled into origin/main; the code itself will
land via the PR merge.

* Python: address PR #5561 review feedback on dependency bounds

Two packaging fixes flagged in review:

1. agent-framework-azure-contentunderstanding: add agent-framework-foundry
   as a runtime dependency. The package's README directs users to
   `pip install agent-framework-azure-contentunderstanding --pre` and the
   basic example imports `FoundryChatClient` from `agent_framework.foundry`,
   so the documented install path was failing with ImportError. Pulling
   agent-framework-foundry into deps makes the advertised entry path
   self-contained.

2. agent-framework-foundry: bump agent-framework-openai lower bound from
   >=1.1.0 to >=1.2.2,<2. Foundry imports private modules from
   agent_framework_openai (`_chat_client.py:22`, `_agent.py:34`), so
   resolvers were free to pair foundry==1.2.2 with older OpenAI versions
   that lack this release's coordinated Responses/history fix. Lockstep the
   floor with the released cohort to prevent mismatched installs.

Both changes pass `validate-dependency-bounds-test` lower + upper at
their respective packages.
f5419b9f38 ยท 2026-04-29 17:51:48 +09:00
History
..

Get Started with Microsoft Agent Framework Copilot Studio

Please install this package via pip:

pip install agent-framework-copilotstudio --pre

Copilot Studio Agent

The Copilot Studio agent enables integration with Microsoft Copilot Studio, allowing you to interact with published copilots through the Agent Framework.

Prerequisites

Before using the Copilot Studio agent, you need:

  1. Copilot Studio Environment: Access to a Microsoft Copilot Studio environment with a published copilot
  2. App Registration: An Azure AD App Registration with appropriate permissions for Power Platform API
  3. Environment Configuration: Set the required environment variables or pass them as parameters

Environment Variables

The following environment variables are used for configuration:

  • COPILOTSTUDIOAGENT__ENVIRONMENTID - Your Copilot Studio environment ID
  • COPILOTSTUDIOAGENT__SCHEMANAME - Your copilot's agent identifier/schema name
  • COPILOTSTUDIOAGENT__AGENTAPPID - Your App Registration client ID
  • COPILOTSTUDIOAGENT__TENANTID - Your Azure AD tenant ID

Basic Usage Example

import asyncio
from agent_framework.microsoft import CopilotStudioAgent

async def main():
    # Create agent using environment variables
    agent = CopilotStudioAgent()

    # Run a simple query
    result = await agent.run("What is the capital of France?")
    print(result)

asyncio.run(main())

Explicit Configuration Example

import asyncio
import os
from agent_framework.microsoft import CopilotStudioAgent, acquire_token
from microsoft_agents.copilotstudio.client import ConnectionSettings, CopilotClient, PowerPlatformCloud, AgentType

async def main():
    # Acquire authentication token
    token = acquire_token(
        client_id=os.environ["COPILOTSTUDIOAGENT__AGENTAPPID"],
        tenant_id=os.environ["COPILOTSTUDIOAGENT__TENANTID"]
    )

    # Create connection settings
    settings = ConnectionSettings(
        environment_id=os.environ["COPILOTSTUDIOAGENT__ENVIRONMENTID"],
        agent_identifier=os.environ["COPILOTSTUDIOAGENT__SCHEMANAME"],
        cloud=PowerPlatformCloud.PROD,
        copilot_agent_type=AgentType.PUBLISHED,
        custom_power_platform_cloud=None
    )

    # Create client and agent
    client = CopilotClient(settings=settings, token=token)
    agent = CopilotStudioAgent(client=client)

    # Run a query
    result = await agent.run("What is the capital of Italy?")
    print(result)

asyncio.run(main())

Authentication

The package uses MSAL (Microsoft Authentication Library) for authentication with interactive flows when needed. Ensure your App Registration has:

  • API Permissions: Power Platform API permissions (https://api.powerplatform.com/.default)
  • Redirect URIs: Configured appropriately for your authentication method
  • Public Client Flows: Enabled if using interactive authentication

Examples

For more comprehensive examples, see the Copilot Studio examples which demonstrate:

  • Basic non-streaming and streaming execution
  • Explicit settings and manual token acquisition
  • Different authentication patterns
  • Error handling and troubleshooting