# ------------------------------------
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# ------------------------------------

"""
DESCRIPTION:
    This sample demonstrates how to use agent operations with toolset from
    the Azure Agents service using a synchronous client.

USAGE:
    python sample_agents_run_with_toolset.py

    Before running the sample:

    pip install azure-ai-agents 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.
"""

import os, sys
from azure.ai.agents import AgentsClient
from azure.identity import DefaultAzureCredential
from azure.ai.agents.models import FunctionTool, ToolSet, CodeInterpreterTool

current_path = os.path.dirname(__file__)
root_path = os.path.abspath(os.path.join(current_path, os.pardir, os.pardir))
if root_path not in sys.path:
    sys.path.insert(0, root_path)
from samples.utils.user_functions import user_functions

agents_client = AgentsClient(
    endpoint=os.environ["PROJECT_ENDPOINT"],
    credential=DefaultAzureCredential(),
)

# Create agent with toolset and process agent run
with agents_client:
    # Initialize agent toolset with user functions and code interpreter
    # [START create_agent_toolset]
    functions = FunctionTool(user_functions)
    code_interpreter = CodeInterpreterTool()

    toolset = ToolSet()
    toolset.add(functions)
    toolset.add(code_interpreter)

    # To enable tool calls executed automatically
    agents_client.enable_auto_function_calls(toolset)

    agent = agents_client.create_agent(
        model=os.environ["MODEL_DEPLOYMENT_NAME"],
        name="my-agent",
        instructions="You are a helpful agent",
        toolset=toolset,
    )
    # [END create_agent_toolset]
    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, send an email with the datetime and weather information in New York?",
    )
    print(f"Created message, ID: {message.id}")

    # Create and process agent run in thread with tools
    # [START create_and_process_run]
    run = agents_client.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)
    # [END create_and_process_run]
    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)
    for msg in messages:
        if msg.text_messages:
            last_text = msg.text_messages[-1]
            print(f"{msg.role}: {last_text.text.value}")
