trustgraph/trustgraph-base/trustgraph/base/document_embeddings_query_service.py
2025-04-22 10:52:11 +01:00

84 lines
2 KiB
Python
Executable file

"""
Document embeddings query service. Input is vectors. Output is list of
embeddings.
"""
from .. schema import DocumentEmbeddingsRequest, DocumentEmbeddingsResponse
from .. schema import Error, Value
from . flow_processor import FlowProcessor
from . consumer_spec import ConsumerSpec
from . producer_spec import ProducerSpec
default_ident = "ge-query"
class DocumentEmbeddingsQueryService(FlowProcessor):
def __init__(self, **params):
id = params.get("id")
super(DocumentEmbeddingsQueryService, self).__init__(
**params | { "id": id }
)
self.register_specification(
ConsumerSpec(
name = "request",
schema = DocumentEmbeddingsRequest,
handler = self.on_message
)
)
self.register_specification(
ProducerSpec(
name = "response",
schema = DocumentEmbeddingsResponse,
)
)
async def on_message(self, msg, consumer, flow):
try:
request = msg.value()
# Sender-produced ID
id = msg.properties()["id"]
print(f"Handling input {id}...", flush=True)
docs = await self.query_document_embeddings(request)
print("Send response...", flush=True)
r = DocumentEmbeddingsResponse(documents=docs, error=None)
await flow("response").send(r, properties={"id": id})
print("Done.", flush=True)
except Exception as e:
print(f"Exception: {e}")
print("Send error response...", flush=True)
r = DocumentEmbeddingsResponse(
error=Error(
type = "document-embeddings-query-error",
message = str(e),
),
response=None,
)
await flow("response").send(r, properties={"id": id})
@staticmethod
def add_args(parser):
FlowProcessor.add_args(parser)
def run():
Processor.launch(default_ident, __doc__)