custom deployment files
Browse files- handler.py +28 -0
- requirements.txt +2 -0
handler.py
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from typing import Dict, List, Any
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from lmdeploy import pipeline
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from lmdeploy.vl import load_image
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from lmdeploy.messages import TurbomindEngineConfig
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class EndpointHandler():
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def __init__(self, path):
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# Preload the model at initialization
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backend_config = TurbomindEngineConfig(model_name ="OpenGVLab/InternVL-Chat-V1-5",model_format='hf',tp=1)
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self.pipe = pipeline(f"{path}", backend_config=backend_config, log_level='INFO')
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def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:
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"""
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data args:
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inputs (:obj: `str` | `PIL.Image` | `np.array`)
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kwargs
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Return:
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A :obj:`list` | `dict`: will be serialized and returned
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"""
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image_url = data.get('image_url')
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if not image_url:
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return {'error': 'No image URL provided'}
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image = load_image(image_url)
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prompt = """Please analyze the provided image to determine if it contains any form of analytical representation, such as a chart, graph, or table. If such a representation is present, extract all the information into a textual, relational data format and provide a detailed description of the image. If the image does not contain any analytical representation, give only "none" without any additional words."""
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response = self.pipe((prompt, image))
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return {'response': response.text}
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requirements.txt
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lmdeploy
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timm
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