mirror of
https://github.com/trustgraph-ai/trustgraph.git
synced 2026-04-26 00:46:22 +02:00
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
31 lines
877 B
Python
31 lines
877 B
Python
|
|
from . request_response_spec import RequestResponse, RequestResponseSpec
|
|
from .. schema import EmbeddingsRequest, EmbeddingsResponse
|
|
|
|
class EmbeddingsClient(RequestResponse):
|
|
async def embed(self, text, timeout=30):
|
|
|
|
resp = await self.request(
|
|
EmbeddingsRequest(
|
|
text = text
|
|
),
|
|
timeout=timeout
|
|
)
|
|
|
|
if resp.error:
|
|
raise RuntimeError(resp.error.message)
|
|
|
|
return resp.vectors
|
|
|
|
class EmbeddingsClientSpec(RequestResponseSpec):
|
|
def __init__(
|
|
self, request_name, response_name,
|
|
):
|
|
super(EmbeddingsClientSpec, self).__init__(
|
|
request_name = request_name,
|
|
request_schema = EmbeddingsRequest,
|
|
response_name = response_name,
|
|
response_schema = EmbeddingsResponse,
|
|
impl = EmbeddingsClient,
|
|
)
|
|
|