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

"""
DESCRIPTION:
    This sample demonstrates how to use basic agent operations using image file input for the
    the Azure Agents service using a synchronous client.

USAGE:
    python sample_agents_image_input_file.py

    Before running the sample:

    pip install azure-ai-projects 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.
"""
import asyncio
import os, time
from typing import List
from azure.ai.projects.aio import AIProjectClient
from azure.identity.aio import DefaultAzureCredential
from azure.ai.agents.models import (
    ListSortOrder,
    MessageTextContent,
    MessageInputContentBlock,
    MessageImageFileParam,
    MessageInputTextBlock,
    MessageInputImageFileBlock,
    FilePurpose,
)

asset_file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../assets/image_file.png"))


async def main():
    project_client = AIProjectClient(
        endpoint=os.environ["PROJECT_ENDPOINT"],
        credential=DefaultAzureCredential(),
    )

    async with project_client:
        agents_client = project_client.agents

        agent = await agents_client.create_agent(
            model=os.environ["MODEL_DEPLOYMENT_NAME"],
            name="my-agent",
            instructions="You are helpful agent",
        )
        print(f"Created agent, agent ID: {agent.id}")

        thread = await agents_client.threads.create()
        print(f"Created thread, thread ID: {thread.id}")

        image_file = await agents_client.files.upload_and_poll(file_path=asset_file_path, purpose=FilePurpose.AGENTS)
        print(f"Uploaded file, file ID: {image_file.id}")

        input_message = "Hello, what is in the image ?"
        file_param = MessageImageFileParam(file_id=image_file.id, detail="high")
        content_blocks: List[MessageInputContentBlock] = [
            MessageInputTextBlock(text=input_message),
            MessageInputImageFileBlock(image_file=file_param),
        ]
        message = await agents_client.messages.create(thread_id=thread.id, role="user", content=content_blocks)
        print(f"Created message, message ID: {message.id}")

        run = await agents_client.runs.create(thread_id=thread.id, agent_id=agent.id)

        # Poll the run as long as run status is queued or in progress
        while run.status in ["queued", "in_progress", "requires_action"]:
            # Wait for a second
            time.sleep(1)
            run = await agents_client.runs.get(thread_id=thread.id, run_id=run.id)
            print(f"Run status: {run.status}")

        if run.status == "failed":
            print(f"Run failed: {run.last_error}")

        await agents_client.delete_agent(agent.id)
        print("Deleted agent")

        messages = agents_client.messages.list(
            thread_id=thread.id,
            order=ListSortOrder.ASCENDING,
        )

        async for msg in messages:
            last_part = msg.content[-1]
            if isinstance(last_part, MessageTextContent):
                print(f"{msg.role}: {last_part.text.value}")


if __name__ == "__main__":
    asyncio.run(main())
