Commit 1a187b0

anthropic = [

"anthropic ~= 0.32"

]

aws = [

"boto3>=1.36.4,<1.38.0",

]

copilot_studio = [

"microsoft-agents-core @ https://test-files.pythonhosted.org/packages/17/ae/c87bfb943e75fac50522e2598232fc386b0d7f09a2dd462bbdc63cb83602/microsoft_agents_core-0.0.0a2-py3-none-any.whl",

"microsoft-agents-copilotstudio-client @ https://test-files.pythonhosted.org/packages/47/de/9f9e0a0c57132363154dcf197bf2ce0ed33e9c986a8df8573091bcc79b54/microsoft_agents_copilotstudio_client-0.0.0a2-py3-none-any.whl"

]

dapr = [

"dapr>=1.14.0",

"dapr-ext-fastapi>=1.14.0",

"flask-dapr>=1.14.0",

google = [

"google-cloud-aiplatform == 1.89.0",

"google-generativeai ~= 0.8"

]

mongo = [

"pymongo >= 4.8.0, < 4.13",

"motor >= 3.3.2,< 3.8.0"

]

notebooks = [

"ipykernel ~= 6.29"

]

pandas = [

"pandas ~= 2.2"

usearch = [

"usearch ~= 2.16",

"pyarrow >= 12.0,< 20.0"

]

weaviate = [

"weaviate-client>=4.10,<5.0",

]

build-backend = "flit_core.buildapi"

This README provides an overview on how to use the [CopilotStudioAgent](../../../semantic_kernel/agents/copilot_studio/copilot_studio_agent.py) within Semantic Kernel.

This agent allows you to interact with Microsoft Copilot Studio agents through programmatic APIs.

1. Python 3.10+

2. Install Semantic Kernel with Copilot Studio dependencies:

```bash

pip install semantic-kernel[copilot_studio]

```

3. An agent created in **Microsoft Copilot Studio**

4. Ability to create an application identity in Azure for a **Public Client/Native App Registration**,

or access to an existing app registration with the `CopilotStudio.Copilots.Invoke` API permission assigned.

1. Go to [Microsoft Copilot Studio](https://copilotstudio.microsoft.com).

2. Create a new **Agent**.

3. Publish your newly created Agent.

4. In Copilot Studio, navigate to:

`Settings` → `Advanced` → `Metadata`

Save the following values:

- `Schema Name` (maps to `agent_identifier`)

- `Environment ID`

You will create a **Native Client Application Identity** (no client secret required).

1. Open [Azure Portal](https://portal.azure.com)

2. Navigate to **Entra ID**

3. Go to **App registrations** → **New registration**

4. Fill out:

- **Name**: Any name you like

- **Supported account types**: `Accounts in this organization directory only`

- **Redirect URI**:

- Platform: `Public client/native (mobile & desktop)`

- URI: `http://localhost`

5. Click **Register**

6. From the **Overview** page, note:

- `Application (client) ID`

- `Directory (tenant) ID`

7. Go to: `Manage` → `API permissions`

- Click **Add permission**

- Choose **APIs my organization uses**

- Search for: **Power Platform API**

If it's not listed, see **Tip** below.

8. Choose:

- **Delegated Permissions**

- Expand `CopilotStudio`

- Select `CopilotStudio.Copilots.Invoke`

9. Click **Add permissions**

10. (Optional) Click **Grant admin consent**

If you **do not see Power Platform API**, follow [Step 2 in Power Platform API Authentication](https://learn.microsoft.com/en-us/power-platform/admin/programmability-authentication-v2) to add the API to your tenant.

Once you've collected all required values:

1. Set the following environment variables in your terminal or .env file:

If all required environment variables are set correctly, you don't need to manually create or pass a `client`. Semantic Kernel will automatically construct the client using the environment configuration.

However, if you need to override any environment variables—such as when specifying custom credentials or cloud settings—you should create the `client` explicitly using `CopilotStudioAgent.create_client(...)` and then pass it to the agent constructor.

client: CopilotClient = CopilotStudioAgent.create_client(

auth_mode: CopilotStudioAgentAuthMode | Literal["interactive", "service"] | None = None,

agent_identifier: str | None = None,

app_client_id: str | None = None,

client_secret: str | None = None,

client_certificate: str | None = None,

cloud: PowerPlatformCloud | None = None,

copilot_agent_type: AgentType | None = None,

custom_power_platform_cloud: str | None = None,

env_file_encoding: str | None = None,

env_file_path: str | None = None,

environment_id: str | None = None,

tenant_id: str | None = None,

user_assertion: str | None = None,

)

agent = CopilotStudioAgent(

client=client,

name="<name>",

instructions="<instructions>",

)

import asyncio

from semantic_kernel.agents import CopilotStudioAgent

async def main() -> None:

# 1. Create the agent

agent = CopilotStudioAgent(

name="PhysicsAgent",

instructions="You help answer questions about physics. ",

)

# 2. Create a list of user inputs

USER_INPUTS = [

"Why is the sky blue?",

"What is the speed of light?",

]

# 3. Loop through the user inputs and get responses from the agent

for user_input in USER_INPUTS:

print(f"# User: {user_input}")

response = await agent.get_response(messages=user_input)

print(f"# {response.name}: {response}")

"""

if __name__ == "__main__":

asyncio.run(main())

import asyncio

from microsoft.agents.copilotstudio.client import (

CopilotClient,

)

from semantic_kernel.agents import CopilotStudioAgent, CopilotStudioAgentThread

async def main() -> None:

# As an example, manually create the client and pass it in to the agent

# 1. Create the client

client: CopilotClient = CopilotStudioAgent.create_client(auth_mode="interactive")

# 2. Create the agent

agent = CopilotStudioAgent(

client=client,

name="PhysicsAgent",

instructions="You are help answer questions about physics.",

)

# 3. Create a list of user inputs

USER_INPUTS = [

"Hello! Who are you? My name is John Doe.",

"What is the speed of light?",

"What have we been talking about?",

"What is my name?",

]

# 4. Create a thread to maintain context between user inputs

# If no thread is provided, a new thread will be created

# and returned in the response

thread: CopilotStudioAgentThread | None = None

# 5. Loop through the user inputs and get responses from the agent

for user_input in USER_INPUTS:

print(f"# User: {user_input}")

response = await agent.get_response(messages=user_input, thread=thread)

print(f"# {response.name}: {response}")

thread = response.thread

# 6. If a thread was created, delete it when done

if thread:

await thread.delete()

"""

if __name__ == "__main__":

asyncio.run(main())