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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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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 = 'DAMO-NLP-SG/VideoLLaMA2-7B' |
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self.model, self.processor, self.tokenizer = model_init(self.model_path) |
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def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]: |
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logging.info(f"Received data: {data}") |
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modal = data.get("modal", "video") |
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modal_path = data.get("modal_path", "") |
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instruct = data.get("instruct", "") |
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logging.info(f"Modal: {modal}, Modal Path: {modal_path}, Instruct: {instruct}") |
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if not modal_path or not instruct: |
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raise ValueError("Both 'modal_path' and 'instruct' must be provided in the input data.") |
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output = mm_infer( |
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self.processor[modal](modal_path), |
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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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