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from typing import Dict, List, Any |
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import sys |
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sys.path.append('./') |
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from videollama2 import model_init, mm_infer |
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from videollama2.utils import disable_torch_init |
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import logging |
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import numpy as np |
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class EndpointHandler: |
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def __init__(self, path: str = ""): |
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""" |
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Initialize the handler by loading the model and any other necessary components. |
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Args: |
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path (str): The path to the model or other necessary files. |
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""" |
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disable_torch_init() |
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self.model_path = 'Aliayub1995/VideoLLaMA2-7B' |
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self.model, self.processor, self.tokenizer = model_init(self.model_path) |
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def __call__(self, video_tensor: np.ndarray) -> List[Dict[str, Any]]: |
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logging.info("Received video tensor") |
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modal = "video" |
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instruct = "Can you explain each scene and provide the exact time of the video in which it happened in this format [start_time: end_time]: Description, [start_time: end_time]: Description ..." |
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output = mm_infer( |
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self.processor[modal](video_tensor), |
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instruct, |
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model=self.model, |
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tokenizer=self.tokenizer, |
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do_sample=False, |
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modal=modal |
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) |
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return [{"output": output}] |
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