import re
from typing import Dict, List, Union

from sglang.srt.managers.schedule_batch import MultimodalProcessorOutput
from sglang.srt.models.kimi_vl import KimiVLForConditionalGeneration
from sglang.srt.multimodal.processors.base_processor import (
    BaseMultimodalProcessor as SGLangBaseProcessor,
)
from sglang.srt.multimodal.processors.base_processor import (
    MultimodalSpecialTokens,
)
from sglang.srt.multimodal.processors.kimi_common import KimiGridMMDataMixin


# Compatible with KimiVLForConditionalGeneration
class KimiVLImageProcessor(KimiGridMMDataMixin, SGLangBaseProcessor):
    models = [KimiVLForConditionalGeneration]
    gpu_image_decode = False  # KimiVL HF processor does not support tensor inputs

    def __init__(self, hf_config, server_args, _processor, *args, **kwargs):
        super().__init__(hf_config, server_args, _processor, *args, **kwargs)
        self.mm_tokens = MultimodalSpecialTokens(
            image_token="<|media_pad|>",
            # TODO: could we convert in MultimodalSpecialTokens?
            image_token_id=hf_config.media_placeholder_token_id,
            image_token_regex=re.compile(r"(?:<\|media_pad\|>)+"),
        ).build(_processor)

    async def process_mm_data_async(
        self,
        image_data: List[Union[str, bytes, Dict]],
        input_text,
        request_obj,
        *args,
        **kwargs,
    ):
        base_output = await self.load_mm_data(
            prompt=input_text,
            image_data=image_data,
            multimodal_tokens=self.mm_tokens,
        )

        mm_items, input_ids, _ = self.process_and_combine_mm_data(
            base_output, self.mm_tokens
        )

        return MultimodalProcessorOutput(
            input_ids=input_ids.tolist(),
            mm_items=mm_items,
            im_token_id=self.mm_tokens.image_token_id,
        )

    def get_mm_data(self, prompt, embeddings, **kwargs):
        img_grid_thw = kwargs.get("img_grid_thw", None)
        return self._build_kimi_mm_data_from_grids(
            prompt=prompt,
            embeddings=embeddings,
            image_token_id=self.mm_tokens.image_token_id,
            img_grid_thw=img_grid_thw,
        )