# Copy from qwen_vl.py, adapted for points-v15-chat

from typing import List, Union

from sglang.srt.managers.schedule_batch import MultimodalProcessorOutput
from sglang.srt.models.points_v15_chat import POINTSV15ChatModel
from sglang.srt.multimodal.processors.qwen_vl import QwenVLImageProcessor


class POINTSV15ChatProcessor(QwenVLImageProcessor):
    models = [POINTSV15ChatModel]

    def __init__(self, hf_config, server_args, _processor, *args, **kwargs):
        # Compatible with POINTSV15Chat
        hf_config.vision_start_token_id = None
        hf_config.vision_end_token_id = None
        hf_config.video_token_id = None

        super().__init__(hf_config, server_args, _processor, *args, **kwargs)

    async def process_mm_data_async(
        self,
        image_data: List[Union[str, bytes]],
        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,
        )