# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

import asyncio
import os
from typing import Any, Callable, Optional, Union

import pytest

from vllm.engine.arg_utils import AsyncEngineArgs, EngineArgs
from vllm.sampling_params import SamplingParams
from vllm.v1.engine.async_llm import AsyncLLM
from vllm.v1.engine.llm_engine import LLMEngine
from vllm.v1.executor.multiproc_executor import MultiprocExecutor


class Mock:
    ...


class CustomMultiprocExecutor(MultiprocExecutor):

    def collective_rpc(self,
                       method: Union[str, Callable],
                       timeout: Optional[float] = None,
                       args: tuple = (),
                       kwargs: Optional[dict] = None,
                       non_block: bool = False,
                       unique_reply_rank: Optional[int] = None) -> list[Any]:
        # Drop marker to show that this was ran
        with open(".marker", "w"):
            ...
        return super().collective_rpc(method, timeout, args, kwargs)


CustomMultiprocExecutorAsync = CustomMultiprocExecutor
MODEL = "Qwen/Qwen3-0.6B"


def test_custom_executor_type_checking():
    with pytest.raises(ValueError):
        engine_args = EngineArgs(
            model=MODEL,
            gpu_memory_utilization=0.2,
            max_model_len=8192,
            distributed_executor_backend=Mock,
        )
        LLMEngine.from_engine_args(engine_args)
    with pytest.raises(ValueError):
        engine_args = AsyncEngineArgs(model=MODEL,
                                      gpu_memory_utilization=0.2,
                                      max_model_len=8192,
                                      distributed_executor_backend=Mock)
        AsyncLLM.from_engine_args(engine_args)


@pytest.mark.parametrize("distributed_executor_backend", [
    CustomMultiprocExecutor,
    "tests.v1.executor.test_executor.CustomMultiprocExecutor"
])
def test_custom_executor(distributed_executor_backend, tmp_path):
    cwd = os.path.abspath(".")
    os.chdir(tmp_path)
    try:
        assert not os.path.exists(".marker")

        engine_args = EngineArgs(
            model=MODEL,
            gpu_memory_utilization=0.2,
            max_model_len=8192,
            distributed_executor_backend=distributed_executor_backend,
            enforce_eager=True,  # reduce test time
        )
        engine = LLMEngine.from_engine_args(engine_args)
        sampling_params = SamplingParams(max_tokens=1)

        engine.add_request("0", "foo", sampling_params)
        engine.step()

        assert os.path.exists(".marker")
    finally:
        os.chdir(cwd)


@pytest.mark.parametrize("distributed_executor_backend", [
    CustomMultiprocExecutorAsync,
    "tests.v1.executor.test_executor.CustomMultiprocExecutorAsync"
])
def test_custom_executor_async(distributed_executor_backend, tmp_path):
    cwd = os.path.abspath(".")
    os.chdir(tmp_path)
    try:
        assert not os.path.exists(".marker")

        engine_args = AsyncEngineArgs(
            model=MODEL,
            gpu_memory_utilization=0.2,
            max_model_len=8192,
            distributed_executor_backend=distributed_executor_backend,
            enforce_eager=True,  # reduce test time
        )
        engine = AsyncLLM.from_engine_args(engine_args)
        sampling_params = SamplingParams(max_tokens=1)

        async def t():
            stream = engine.generate(request_id="0",
                                     prompt="foo",
                                     sampling_params=sampling_params)
            async for x in stream:
                ...

        asyncio.run(t())

        assert os.path.exists(".marker")
    finally:
        os.chdir(cwd)
