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https://github.com/trustgraph-ai/trustgraph.git
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a9197d11ee
- Keeps processing in different flows separate so that data can go to different stores / collections etc. - Potentially supports different processing flows - Tidies the processing API with common base-classes for e.g. LLMs, and automatic configuration of 'clients' to use the right queue names in a flow
50 lines
1 KiB
Python
50 lines
1 KiB
Python
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"""
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Document embeddings store base class
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"""
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from .. schema import DocumentEmbeddings
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from .. base import FlowProcessor, ConsumerSpec
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from .. exceptions import TooManyRequests
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default_ident = "document-embeddings-write"
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class DocumentEmbeddingsStoreService(FlowProcessor):
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def __init__(self, **params):
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id = params.get("id")
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super(DocumentEmbeddingsStoreService, self).__init__(
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**params | { "id": id }
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)
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self.register_specification(
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ConsumerSpec(
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name = "input",
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schema = DocumentEmbeddings,
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handler = self.on_message
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)
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)
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async def on_message(self, msg, consumer, flow):
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try:
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request = msg.value()
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await self.store_document_embeddings(request)
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except TooManyRequests as e:
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raise e
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except Exception as e:
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print(f"Exception: {e}")
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raise e
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@staticmethod
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def add_args(parser):
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FlowProcessor.add_args(parser)
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