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# pylint: disable=line-too-long,useless-suppression
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_agents_sharepoint.py
DESCRIPTION:
This sample demonstrates how to use agent operations with the
Sharepoint tool from the Azure Agents service using a synchronous client.
The sharepoint tool is currently available only to whitelisted customers.
For access and onboarding instructions, please contact azureagents-preview@microsoft.com.
USAGE:
python sample_agents_sharepoint.py
Before running the sample:
pip install azure-identity
pip install --pre azure-ai-projects
Set this 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.
3) SHAREPOINT_CONNECTION_NAME - The name of a connection to the SharePoint resource as it is
listed in Azure AI Foundry connected resources.
"""
import os
from azure.ai.projects import AIProjectClient
from azure.identity import DefaultAzureCredential
from azure.ai.agents.models import ListSortOrder, SharepointTool
project_client = AIProjectClient(
endpoint=os.environ["PROJECT_ENDPOINT"],
credential=DefaultAzureCredential(),
)
conn_id = project_client.connections.get(os.environ["SHAREPOINT_CONNECTION_NAME"]).id
# Initialize Sharepoint tool with connection id
sharepoint = SharepointTool(connection_id=conn_id)
# Create agent with Sharepoint tool and process agent run
with project_client:
agents_client = project_client.agents
agent = agents_client.create_agent(
model=os.environ["MODEL_DEPLOYMENT_NAME"],
name="my-agent",
instructions="You are a helpful agent",
tools=sharepoint.definitions,
)
print(f"Created agent, ID: {agent.id}")
# Create thread for communication
thread = agents_client.threads.create()
print(f"Created thread, ID: {thread.id}")
# Create message to thread
message = agents_client.messages.create(
thread_id=thread.id,
role="user",
content="Hello, summarize the key points of the <sharepoint_resource_document>",
)
print(f"Created message, ID: {message.id}")
# Create and process agent run in thread with tools
run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
print(f"Run finished with status: {run.status}")
if run.status == "failed":
print(f"Run failed: {run.last_error}")
# Delete the agent when done
agents_client.delete_agent(agent.id)
print("Deleted agent")
# Fetch and log all messages
messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
for msg in messages:
if msg.text_messages:
responses = []
for text_message in msg.text_messages:
responses.append(text_message.text.value)
message = " ".join(responses)
for annotation in msg.url_citation_annotations:
message = message.replace(
annotation.text, f" [{annotation.url_citation.title}]({annotation.url_citation.url})"
)
print(f"{msg.role}: {message}")
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