# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from abc import ABC, abstractmethod
from collections.abc import AsyncGenerator, Sequence
from typing import Generic, TypeVar

from vllm.config import VllmConfig
from vllm.inputs import PromptType
from vllm.outputs import PoolingRequestOutput
from vllm.pooling_params import PoolingParams
from vllm.renderers import BaseRenderer
from vllm.sampling_params import SamplingParams

IOProcessorInput = TypeVar("IOProcessorInput")
IOProcessorOutput = TypeVar("IOProcessorOutput")


class IOProcessor(ABC, Generic[IOProcessorInput, IOProcessorOutput]):
    """Abstract interface for pre/post-processing of engine I/O."""

    def __init__(self, vllm_config: VllmConfig, renderer: BaseRenderer):
        super().__init__()

        self.vllm_config = vllm_config

    def parse_data(self, data: object) -> IOProcessorInput:
        raise NotImplementedError

    def merge_sampling_params(
        self,
        params: SamplingParams | None = None,
    ) -> SamplingParams:
        return params or SamplingParams()

    def merge_pooling_params(
        self,
        params: PoolingParams | None = None,
    ) -> PoolingParams:
        return params or PoolingParams(task="plugin")

    @abstractmethod
    def pre_process(
        self,
        prompt: IOProcessorInput,
        request_id: str | None = None,
        **kwargs,
    ) -> PromptType | Sequence[PromptType]:
        raise NotImplementedError

    async def pre_process_async(
        self,
        prompt: IOProcessorInput,
        request_id: str | None = None,
        **kwargs,
    ) -> PromptType | Sequence[PromptType]:
        return self.pre_process(prompt, request_id, **kwargs)

    @abstractmethod
    def post_process(
        self,
        model_output: Sequence[PoolingRequestOutput],
        request_id: str | None = None,
        **kwargs,
    ) -> IOProcessorOutput:
        raise NotImplementedError

    async def post_process_async(
        self,
        model_output: AsyncGenerator[tuple[int, PoolingRequestOutput]],
        request_id: str | None = None,
        **kwargs,
    ) -> IOProcessorOutput:
        # We cannot guarantee outputs are returned in the same order they were
        # fed to vLLM.
        # Let's sort them by id before post_processing
        sorted_output = sorted(
            [(i, item) async for i, item in model_output], key=lambda output: output[0]
        )
        collected_output = [output[1] for output in sorted_output]
        return self.post_process(collected_output, request_id=request_id, **kwargs)