# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

import json
import logging
import os
import shutil

import pytest

from tests.conftest import NatsServer
from tests.fault_tolerance.etcd_ha.utils import (
    DynamoFrontendProcess,
    EtcdCluster,
    send_inference_request,
    wait_for_processes_to_terminate,
)
from tests.utils.constants import FAULT_TOLERANCE_MODEL_NAME
from tests.utils.engine_process import FRONTEND_PORT
from tests.utils.managed_process import ManagedProcess
from tests.utils.payloads import check_health_generate, check_models_api

logger = logging.getLogger(__name__)

pytestmark = [
    pytest.mark.fault_tolerance,
    pytest.mark.vllm,
]


class DynamoWorkerProcess(ManagedProcess):
    """Process manager for Dynamo worker with vLLM backend and ETCD HA support"""

    def __init__(self, request, etcd_endpoints: list, is_prefill: bool = False):
        command = [
            "python3",
            "-m",
            "dynamo.vllm",
            "--model",
            FAULT_TOLERANCE_MODEL_NAME,
            "--enforce-eager",
            "--gpu-memory-utilization",
            "0.45",
            "--max-model-len",
            "8192",
        ]

        # Set port based on worker type
        port = "8082" if is_prefill else "8081"

        # Configure health check based on worker type
        if is_prefill:
            # Prefill workers check their own status endpoint
            command.append("--is-prefill-worker")
            health_check_urls = [(f"http://localhost:{port}/health", self.is_ready)]
        else:
            # Decode workers should also check their own status endpoint first,
            # then verify the frontend sees the model
            health_check_urls = [
                (f"http://localhost:{port}/health", self.is_ready),
                (f"http://localhost:{FRONTEND_PORT}/v1/models", check_models_api),
                (f"http://localhost:{FRONTEND_PORT}/health", check_health_generate),
            ]

        # Set debug logging and ETCD endpoints
        env = os.environ.copy()
        env["DYN_LOG"] = "debug"
        env["ETCD_ENDPOINTS"] = ",".join(etcd_endpoints)
        env["DYN_SYSTEM_USE_ENDPOINT_HEALTH_STATUS"] = '["generate"]'
        env["DYN_SYSTEM_PORT"] = port

        if is_prefill:
            command.extend(
                [
                    "--kv-events-config",
                    json.dumps(
                        {
                            "publisher": "zmq",
                            "topic": "kv-events",
                            "endpoint": "tcp://*:20082",
                            "enable_kv_cache_events": True,
                        }
                    ),
                ]
            )
            env["VLLM_NIXL_SIDE_CHANNEL_PORT"] = "5601"

        # Set log directory based on worker type
        worker_type = "prefill_worker" if is_prefill else "worker"
        log_dir = f"{request.node.name}_{worker_type}"

        # Clean up any existing log directory from previous runs
        try:
            shutil.rmtree(log_dir)
            logger.info(f"Cleaned up existing log directory: {log_dir}")
        except FileNotFoundError:
            pass

        super().__init__(
            command=command,
            env=env,
            health_check_urls=health_check_urls,
            timeout=120,
            display_output=True,
            terminate_all_matching_process_names=False,
            stragglers=[
                "VLLM::EngineCore",
            ],
            straggler_commands=[
                "-m dynamo.vllm",
            ],
            log_dir=log_dir,
        )

        self.is_prefill = is_prefill

    def is_ready(self, response) -> bool:
        """Check the health of the worker process"""
        try:
            data = response.json()
            if data.get("status") == "ready":
                worker_type = "Prefill worker" if self.is_prefill else "Worker"
                logger.info(f"{worker_type} status is ready")
                return True
            worker_type = "Prefill worker" if self.is_prefill else "Worker"
            logger.warning(f"{worker_type} status is not ready: {data.get('status')}")
        except ValueError:
            worker_type = "Prefill worker" if self.is_prefill else "Worker"
            logger.warning(f"{worker_type} health response is not valid JSON")
        return False


@pytest.mark.gpu_1
@pytest.mark.e2e
@pytest.mark.model(FAULT_TOLERANCE_MODEL_NAME)
@pytest.mark.nightly
@pytest.mark.timeout(600)
def test_etcd_ha_failover_vllm_aggregated(request, predownload_models):
    """
    Test ETCD High Availability with repeated node failures and recoveries.

    This test:
    1. Starts a 3-node ETCD cluster
    2. Starts NATS, frontend, and a vLLM worker
    3. Cycles through each of the 3 replicas:
       - Terminate the replica by index
       - Send inference request to verify system still works
       - Restart the terminated node

    This ensures testing of:
    - ETCD leader termination
    - Frontend/worker disconnection from their connected ETCD replica
    """
    # Step 1: Start NATS server
    with NatsServer(request):
        logger.info("NATS server started successfully")

        # Step 2: Start 3-node ETCD cluster
        num_replicas = 3
        with EtcdCluster(request, num_replicas=num_replicas) as etcd_cluster:
            logger.info("3-node ETCD cluster started successfully")

            # Get the endpoints for all ETCD nodes
            etcd_endpoints = etcd_cluster.get_client_endpoints()
            logger.info(f"ETCD endpoints: {etcd_endpoints}")

            # Step 3: Start the frontend with ETCD endpoints
            with DynamoFrontendProcess(request, etcd_endpoints):
                logger.info("Frontend started successfully")

                # Step 4: Start a vLLM worker
                with DynamoWorkerProcess(request, etcd_endpoints):
                    logger.info("Worker started successfully")

                    # Step 5: Send initial inference request to verify system is working
                    logger.info("Sending initial inference request")
                    result = send_inference_request("What is 2+2? The answer is")
                    assert (
                        "4" in result.lower() or "four" in result.lower()
                    ), f"Expected '4' or 'four' in response, got: '{result}'"

                    # Step 6: Cycle through each replica to terminate/verify/restart
                    for i in range(num_replicas):
                        # Terminate a replica
                        logger.info(f"Iteration {i}: Terminating replica etcd-{i}")
                        etcd_cluster.terminate_replica(i)

                        # Send inference request to verify system still works
                        logger.info(
                            f"Iteration {i}: Sending inference request after termination"
                        )
                        result = send_inference_request(
                            "The capital of France is", max_tokens=20
                        )
                        assert (
                            "paris" in result.lower()
                        ), f"Iteration {i}: Expected 'Paris' in response, got: '{result}'"

                        # Restart the terminated replica
                        logger.info(f"Iteration {i}: Restarting replica etcd-{i}")
                        etcd_cluster.restart_replica(i)


@pytest.mark.gpu_1
@pytest.mark.e2e
@pytest.mark.nightly
@pytest.mark.model(FAULT_TOLERANCE_MODEL_NAME)
@pytest.mark.timeout(600)
def test_etcd_ha_failover_vllm_disaggregated(
    request, predownload_models, set_ucx_tls_no_mm
):
    """
    Test ETCD High Availability with repeated node failures and recoveries in disaggregated mode.

    This test:
    1. Starts a 3-node ETCD cluster
    2. Starts NATS, frontend, and both prefill and decode vLLM workers
    3. Cycles through each of the 3 replicas:
       - Terminate the replica by index
       - Send inference request to verify system still works
       - Restart the terminated node

    This ensures testing of:
    - ETCD leader termination
    - Frontend/worker disconnection from their connected ETCD replica
    """
    # Step 1: Start NATS server
    with NatsServer(request):
        logger.info("NATS server started successfully")

        # Step 2: Start 3-node ETCD cluster
        num_replicas = 3
        with EtcdCluster(request, num_replicas=num_replicas) as etcd_cluster:
            logger.info("3-node ETCD cluster started successfully")

            # Get the endpoints for all ETCD nodes
            etcd_endpoints = etcd_cluster.get_client_endpoints()
            logger.info(f"ETCD endpoints: {etcd_endpoints}")

            # Step 3: Start the frontend with ETCD endpoints
            with DynamoFrontendProcess(request, etcd_endpoints):
                logger.info("Frontend started successfully")

                # Step 4: Start the prefill worker
                with DynamoWorkerProcess(request, etcd_endpoints, is_prefill=True):
                    logger.info("Prefill worker started successfully")

                    # Step 5: Start the decode worker
                    with DynamoWorkerProcess(request, etcd_endpoints, is_prefill=False):
                        logger.info("Decode worker started successfully")

                        # Step 6: Send initial inference request to verify system is working
                        logger.info("Sending initial inference request")
                        result = send_inference_request("What is 2+2? The answer is")
                        assert (
                            "4" in result.lower() or "four" in result.lower()
                        ), f"Expected '4' or 'four' in response, got: '{result}'"

                        # Step 7: Cycle through each replica to terminate/verify/restart
                        for i in range(num_replicas):
                            # Terminate a replica
                            logger.info(f"Iteration {i}: Terminating replica etcd-{i}")
                            etcd_cluster.terminate_replica(i)

                            # Send inference request to verify system still works
                            logger.info(
                                f"Iteration {i}: Sending inference request after termination"
                            )
                            result = send_inference_request(
                                "The capital of France is", max_tokens=20
                            )
                            assert (
                                "paris" in result.lower()
                            ), f"Iteration {i}: Expected 'Paris' in response, got: '{result}'"

                            # Restart the terminated replica
                            logger.info(f"Iteration {i}: Restarting replica etcd-{i}")
                            etcd_cluster.restart_replica(i)


@pytest.mark.gpu_1
@pytest.mark.e2e
@pytest.mark.nightly
@pytest.mark.model(FAULT_TOLERANCE_MODEL_NAME)
@pytest.mark.timeout(600)
def test_etcd_non_ha_shutdown_vllm_aggregated(request, predownload_models):
    """
    Test that frontend and worker shut down when single ETCD node is terminated.

    This test:
    1. Starts a single ETCD node (no cluster)
    2. Starts NATS, frontend, and a vLLM worker
    3. Sends an inference request to verify the system works
    4. Terminates the single ETCD node
    5. Verifies that frontend and worker shut down gracefully
    """
    # Step 1: Start NATS server
    with NatsServer(request):
        logger.info("NATS server started successfully")

        # Step 2: Start single ETCD node using EtcdCluster with num_replicas=1
        with EtcdCluster(request, num_replicas=1) as etcd_cluster:
            logger.info("Single ETCD node started successfully")

            # Get the endpoint for the single ETCD node
            etcd_endpoints = etcd_cluster.get_client_endpoints()
            logger.info(f"ETCD endpoint: {etcd_endpoints}")

            # Step 3: Start the frontend with ETCD endpoint
            with DynamoFrontendProcess(request, etcd_endpoints) as frontend:
                logger.info("Frontend started successfully")

                # Step 4: Start a vLLM worker
                with DynamoWorkerProcess(request, etcd_endpoints) as worker:
                    logger.info("Worker started successfully")

                    # Step 5: Send inference request to verify system is working
                    logger.info("Sending inference request")
                    result = send_inference_request("What is 2+2? The answer is")
                    assert (
                        "4" in result.lower() or "four" in result.lower()
                    ), f"Expected '4' or 'four' in response, got: '{result}'"

                    logger.info("System is working correctly with single ETCD node")

                    # Step 6: Terminate the ETCD node
                    logger.info("Terminating single ETCD node")
                    etcd_cluster.stop()

                    # Step 7: Wait and verify frontend and worker detect the loss
                    wait_for_processes_to_terminate(
                        {"Worker": worker, "Frontend": frontend}
                    )


@pytest.mark.gpu_1
@pytest.mark.e2e
@pytest.mark.nightly
@pytest.mark.model(FAULT_TOLERANCE_MODEL_NAME)
@pytest.mark.timeout(600)
def test_etcd_non_ha_shutdown_vllm_disaggregated(
    request, predownload_models, set_ucx_tls_no_mm
):
    """
    Test that frontend and workers shut down when single ETCD node is terminated in disaggregated mode.

    This test:
    1. Starts a single ETCD node (no cluster)
    2. Starts NATS, frontend, and both prefill and decode vLLM workers
    3. Sends an inference request to verify the system works
    4. Terminates the single ETCD node
    5. Verifies that frontend and both workers shut down gracefully
    """
    # Step 1: Start NATS server
    with NatsServer(request):
        logger.info("NATS server started successfully")

        # Step 2: Start single ETCD node using EtcdCluster with num_replicas=1
        with EtcdCluster(request, num_replicas=1) as etcd_cluster:
            logger.info("Single ETCD node started successfully")

            # Get the endpoint for the single ETCD node
            etcd_endpoints = etcd_cluster.get_client_endpoints()
            logger.info(f"ETCD endpoint: {etcd_endpoints}")

            # Step 3: Start the frontend with ETCD endpoint
            with DynamoFrontendProcess(request, etcd_endpoints) as frontend:
                logger.info("Frontend started successfully")

                # Step 4: Start the prefill worker
                with DynamoWorkerProcess(
                    request, etcd_endpoints, is_prefill=True
                ) as prefill_worker:
                    logger.info("Prefill worker started successfully")

                    # Step 5: Start the decode worker
                    with DynamoWorkerProcess(
                        request, etcd_endpoints, is_prefill=False
                    ) as decode_worker:
                        logger.info("Decode worker started successfully")

                        # Step 6: Send inference request to verify system is working
                        logger.info("Sending inference request")
                        result = send_inference_request("What is 2+2? The answer is")
                        assert (
                            "4" in result.lower() or "four" in result.lower()
                        ), f"Expected '4' or 'four' in response, got: '{result}'"

                        logger.info(
                            "System is working correctly with single ETCD node in disaggregated mode"
                        )

                        # Step 7: Terminate the ETCD node
                        logger.info("Terminating single ETCD node")
                        etcd_cluster.stop()

                        # Step 8: Wait and verify frontend and both workers detect the loss
                        wait_for_processes_to_terminate(
                            {
                                "Decode Worker": decode_worker,
                                "Prefill Worker": prefill_worker,
                                "Frontend": frontend,
                            }
                        )
