mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-07-17 09:11:03 +02:00
63 lines
1.4 KiB
Python
Executable file
63 lines
1.4 KiB
Python
Executable file
|
|
"""
|
|
Embeddings service, applies an embeddings model selected from HuggingFace.
|
|
Input is text, output is embeddings vector.
|
|
"""
|
|
|
|
from ... schema import EmbeddingsRequest, EmbeddingsResponse
|
|
from ... base import RequestResponseService
|
|
|
|
from fastembed import TextEmbedding
|
|
import os
|
|
|
|
module = "embeddings"
|
|
|
|
default_subscriber = module
|
|
default_model="sentence-transformers/all-MiniLM-L6-v2"
|
|
|
|
class Processor(RequestResponseService):
|
|
|
|
def __init__(self, **params):
|
|
|
|
model = params.get("model", default_model)
|
|
|
|
super(Processor, self).__init__(
|
|
**params | {
|
|
"model": model,
|
|
"request_schema": EmbeddingsRequest,
|
|
"response_schema": EmbeddingsResponse,
|
|
}
|
|
)
|
|
|
|
self.embeddings = TextEmbedding(model_name = model)
|
|
|
|
async def on_request(self, request, consumer, flow):
|
|
|
|
text = request.text
|
|
vecs = self.embeddings.embed([text])
|
|
|
|
vecs = [
|
|
v.tolist()
|
|
for v in vecs
|
|
]
|
|
|
|
return EmbeddingsResponse(
|
|
vectors=list(vecs),
|
|
error=None,
|
|
)
|
|
|
|
@staticmethod
|
|
def add_args(parser):
|
|
|
|
RequestResponseService.add_args(parser, default_subscriber)
|
|
|
|
parser.add_argument(
|
|
'-m', '--model',
|
|
default=default_model,
|
|
help=f'Embeddings model (default: {default_model})'
|
|
)
|
|
|
|
def run():
|
|
|
|
Processor.launch(module, __doc__)
|
|
|