mirror of
https://github.com/trustgraph-ai/trustgraph.git
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a1c95f9745
Add type annotations to 23 modules covering: - Metrics classes (ConsumerMetrics, ProducerMetrics, etc.) - Spec classes (ConsumerSpec, ProducerSpec, SubscriberSpec, etc.) - Service classes with add_args() and run() methods - Utility functions (logging, pubsub, clients) - AsyncProcessor methods All 93 public functions now fully typed. Refs #785
104 lines
2.8 KiB
Python
104 lines
2.8 KiB
Python
from __future__ import annotations
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from argparse import ArgumentParser
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"""
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Document embeddings query service. Input is vectors. Output is list of
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embeddings.
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"""
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import logging
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from argparse import ArgumentParser
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from .. schema import DocumentEmbeddingsRequest, DocumentEmbeddingsResponse
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from .. schema import Error, Term
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from argparse import ArgumentParser
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from . flow_processor import FlowProcessor
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from . consumer_spec import ConsumerSpec
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from . producer_spec import ProducerSpec
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from argparse import ArgumentParser
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# Module logger
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logger = logging.getLogger(__name__)
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default_ident = "doc-embeddings-query"
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default_concurrency = 10
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class DocumentEmbeddingsQueryService(FlowProcessor):
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def __init__(self, **params):
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id = params.get("id")
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concurrency = params.get("concurrency", default_concurrency)
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super(DocumentEmbeddingsQueryService, 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 = "request",
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schema = DocumentEmbeddingsRequest,
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handler = self.on_message,
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concurrency = concurrency,
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)
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)
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self.register_specification(
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ProducerSpec(
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name = "response",
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schema = DocumentEmbeddingsResponse,
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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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# Sender-produced ID
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id = msg.properties()["id"]
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logger.debug(f"Handling document embeddings query request {id}...")
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docs = await self.query_document_embeddings(request)
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logger.debug("Sending document embeddings query response...")
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r = DocumentEmbeddingsResponse(chunks=docs, error=None)
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await flow("response").send(r, properties={"id": id})
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logger.debug("Document embeddings query request completed")
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except Exception as e:
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logger.error(f"Exception in document embeddings query service: {e}", exc_info=True)
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logger.info("Sending error response...")
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r = DocumentEmbeddingsResponse(
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error=Error(
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type = "document-embeddings-query-error",
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message = str(e),
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),
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chunks=[],
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)
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await flow("response").send(r, properties={"id": id})
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@staticmethod
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def add_args(parser: ArgumentParser) -> None:
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FlowProcessor.add_args(parser)
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parser.add_argument(
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'-c', '--concurrency',
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type=int,
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default=default_concurrency,
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help=f'Number of concurrent requests (default: {default_concurrency})'
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)
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def run() -> None:
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Processor.launch(default_ident, __doc__)
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