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56 lines
1.1 KiB
Python
Executable file
56 lines
1.1 KiB
Python
Executable file
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"""
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Embeddings service, applies an embeddings model using fastembed
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Input is text, output is embeddings vector.
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"""
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import logging
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from ... base import EmbeddingsService
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from fastembed import TextEmbedding
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# Module logger
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logger = logging.getLogger(__name__)
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default_ident = "embeddings"
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default_model="sentence-transformers/all-MiniLM-L6-v2"
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class Processor(EmbeddingsService):
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def __init__(self, **params):
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model = params.get("model", default_model)
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super(Processor, self).__init__(
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**params | { "model": model }
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)
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logger.info("Loading FastEmbed model...")
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self.embeddings = TextEmbedding(model_name = model)
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async def on_embeddings(self, text):
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vecs = self.embeddings.embed([text])
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return [
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v.tolist()
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for v in vecs
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]
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@staticmethod
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def add_args(parser):
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EmbeddingsService.add_args(parser)
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parser.add_argument(
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'-m', '--model',
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default=default_model,
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help=f'Embeddings model (default: {default_model})'
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)
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def run():
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Processor.launch(default_ident, __doc__)
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