# 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 file search tools and iteration in streaming from
    the Azure Agents service using a synchronous client.

USAGE:
    python sample_agents_stream_iteration_with_file_search.py

    Before running the sample:

    pip install azure-ai-projects 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
from azure.ai.projects import AIProjectClient
from azure.ai.agents.models import AgentStreamEvent, FileSearchTool, RunStepDeltaChunk
from azure.ai.agents.models import MessageDeltaChunk, RunStep, ThreadMessage, ThreadRun, FilePurpose, ListSortOrder
from azure.identity import DefaultAzureCredential

asset_file_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../assets/product_info_1.md"))

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

with project_client:
    agents_client = project_client.agents

    # Upload file and create vector store
    file = agents_client.files.upload_and_poll(file_path=asset_file_path, purpose=FilePurpose.AGENTS)
    print(f"Uploaded file, file ID: {file.id}")

    vector_store = agents_client.vector_stores.create_and_poll(file_ids=[file.id], name="my_vectorstore")
    print(f"Created vector store, vector store ID: {vector_store.id}")

    # Create file search tool with resources followed by creating agent
    file_search = FileSearchTool(vector_store_ids=[vector_store.id])

    agent = agents_client.create_agent(
        model=os.environ["MODEL_DEPLOYMENT_NAME"],
        name="my-agent",
        instructions="Hello, you are helpful agent and can search information from uploaded files",
        tools=file_search.definitions,
        tool_resources=file_search.resources,
    )
    print(f"Created agent, agent ID: {agent.id}")

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

    message = agents_client.messages.create(
        thread_id=thread.id, role="user", content="What feature does Smart Eyewear offer?"
    )
    print(f"Created message, message ID {message.id}")

    with agents_client.runs.stream(thread_id=thread.id, agent_id=agent.id) as stream:

        for event_type, event_data, _ in stream:

            if isinstance(event_data, MessageDeltaChunk):
                print(f"Text delta received: {event_data.text}")

            elif isinstance(event_data, RunStepDeltaChunk):
                print(f"RunStepDeltaChunk received. ID: {event_data.id}.")

            elif isinstance(event_data, ThreadMessage):
                print(f"ThreadMessage created. ID: {event_data.id}, Status: {event_data.status}")
                for annotation in event_data.file_citation_annotations:
                    print(
                        f"Citation {annotation.text} from file ID: {annotation.file_citation.file_id}, start index: {annotation.start_index}, end index: {annotation.end_index}"
                    )

            elif isinstance(event_data, ThreadRun):
                print(f"ThreadRun status: {event_data.status}")

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

            elif isinstance(event_data, RunStep):
                print(f"RunStep type: {event_data.type}, Status: {event_data.status}")

            elif event_type == AgentStreamEvent.ERROR:
                print(f"An error occurred. Data: {event_data}")

            elif event_type == AgentStreamEvent.DONE:
                print("Stream completed.")

            else:
                print(f"Unhandled Event Type: {event_type}, Data: {event_data}")

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

    messages = agents_client.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
    for msg in messages:
        if msg.text_messages:
            last_text = msg.text_messages[-1]
            print(f"{msg.role}: {last_text.text.value}")
