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# pylint: disable=line-too-long,useless-suppression
# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------
"""
DESCRIPTION:
This sample demonstrates how to use agent operations with the Browser Automation tool from
the Azure Agents service using a synchronous client.
USAGE:
python sample_agents_browser_automation.py
Before running the sample:
pip install azure-ai-agents --pre
pip install azure-ai-projects azure-identity
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.
3) AZURE_PLAYWRIGHT_CONNECTION_NAME - The name of a connection to the Azure Playwright Workspace as it is
listed in Azure AI Foundry connected resources.
"""
import os
from azure.ai.projects import AIProjectClient
from azure.ai.agents.models import (
MessageRole,
RunStepToolCallDetails,
BrowserAutomationTool,
RunStepBrowserAutomationToolCall,
)
from azure.identity import DefaultAzureCredential
project_client = AIProjectClient(endpoint=os.environ["PROJECT_ENDPOINT"], credential=DefaultAzureCredential())
# [START create_agent_with_browser_automation]
connection_id = project_client.connections.get(os.environ["AZURE_PLAYWRIGHT_CONNECTION_NAME"]).id
# Initialize Browser Automation tool and add the connection id
browser_automation = BrowserAutomationTool(connection_id=connection_id)
with project_client:
agents_client = project_client.agents
# Create a new Agent that has the Browser Automation tool attached.
# Note: To add Browser Automation tool to an existing Agent with an `agent_id`, do the following:
# agent = agents_client.update_agent(agent_id, tools=browser_automation.definitions)
agent = agents_client.create_agent(
model=os.environ["MODEL_DEPLOYMENT_NAME"],
name="my-agent",
instructions="""
You are an Agent helping with browser automation tasks.
You can answer questions, provide information, and assist with various tasks
related to web browsing using the Browser Automation tool available to you.
""",
tools=browser_automation.definitions,
)
# [END create_agent_with_browser_automation]
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=MessageRole.USER,
content="""
Your goal is to report the percent of Microsoft year-to-date stock price change.
To do that, go to the website finance.yahoo.com.
At the top of the page, you will find a search bar.
Enter the value 'MSFT', to get information about the Microsoft stock price.
At the top of the resulting page you will see a default chart of Microsoft stock price.
Click on 'YTD' at the top of that chart, and report the percent value that shows up just below it.
""",
)
print(f"Created message, ID: {message.id}")
# Create and process agent run in thread with tools
print(f"Waiting for Agent run to complete. Please wait...")
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}")
# Fetch run steps to get the details of the agent run
run_steps = agents_client.run_steps.list(thread_id=thread.id, run_id=run.id)
for step in run_steps:
print(f"Step {step.id} status: {step.status}")
if isinstance(step.step_details, RunStepToolCallDetails):
print(" Tool calls:")
tool_calls = step.step_details.tool_calls
for call in tool_calls:
print(f" Tool call ID: {call.id}")
print(f" Tool call type: {call.type}")
if isinstance(call, RunStepBrowserAutomationToolCall):
print(f" Browser automation input: {call.browser_automation.input}")
print(f" Browser automation output: {call.browser_automation.output}")
print(" Steps:")
for tool_step in call.browser_automation.steps:
print(f" Last step result: {tool_step.last_step_result}")
print(f" Current state: {tool_step.current_state}")
print(f" Next step: {tool_step.next_step}")
print() # add an extra newline between tool steps
print() # add an extra newline between tool calls
print() # add an extra newline between run steps
# Optional: Delete the agent once the run is finished.
# Comment out this line if you plan to reuse the agent later.
agents_client.delete_agent(agent.id)
print("Deleted agent")
# Print the Agent's response message with optional citation
response_message = agents_client.messages.get_last_message_by_role(thread_id=thread.id, role=MessageRole.AGENT)
if response_message:
for text_message in response_message.text_messages:
print(f"Agent response: {text_message.text.value}")
for annotation in response_message.url_citation_annotations:
print(f"URL Citation: [{annotation.url_citation.title}]({annotation.url_citation.url})")
|
