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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
61 lines
1.7 KiB
Python
61 lines
1.7 KiB
Python
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from . request_response_spec import RequestResponse, RequestResponseSpec
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from .. schema import TriplesQueryRequest, TriplesQueryResponse, Value
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from .. knowledge import Uri, Literal
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class Triple:
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def __init__(self, s, p, o):
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self.s = s
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self.p = p
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self.o = o
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def to_value(x):
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if x.is_uri: return Uri(x.value)
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return Literal(x.value)
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def from_value(x):
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if x is None: return None
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if isinstance(x, Uri):
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return Value(value=str(x), is_uri=True)
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else:
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return Value(value=str(x), is_uri=False)
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class TriplesClient(RequestResponse):
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async def query(self, s=None, p=None, o=None, limit=20,
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user="trustgraph", collection="default",
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timeout=30):
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resp = await self.request(
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TriplesQueryRequest(
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s = from_value(s),
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p = from_value(p),
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o = from_value(o),
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limit = limit,
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user = user,
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collection = collection,
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),
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timeout=timeout
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)
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if resp.error:
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raise RuntimeError(resp.error.message)
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triples = [
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Triple(to_value(v.s), to_value(v.p), to_value(v.o))
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for v in resp.triples
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]
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return triples
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class TriplesClientSpec(RequestResponseSpec):
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def __init__(
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self, request_name, response_name,
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):
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super(TriplesClientSpec, self).__init__(
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request_name = request_name,
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request_schema = TriplesQueryRequest,
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response_name = response_name,
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response_schema = TriplesQueryResponse,
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impl = TriplesClient,
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)
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