mirror of
https://github.com/trustgraph-ai/trustgraph.git
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b0f4c58200
* Update schema defs for source -> metadata * Migrate to use metadata part of schema, also add metadata to triples & vecs * Add user/collection metadata to query * Use user/collection in RAG * Write and query working on triples
267 lines
7.2 KiB
Python
267 lines
7.2 KiB
Python
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from . clients.graph_embeddings_client import GraphEmbeddingsClient
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from . clients.triples_query_client import TriplesQueryClient
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from . clients.embeddings_client import EmbeddingsClient
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from . clients.prompt_client import PromptClient
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from . schema import GraphEmbeddingsRequest, GraphEmbeddingsResponse
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from . schema import TriplesQueryRequest, TriplesQueryResponse
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from . schema import prompt_request_queue
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from . schema import prompt_response_queue
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from . schema import embeddings_request_queue
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from . schema import embeddings_response_queue
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from . schema import graph_embeddings_request_queue
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from . schema import graph_embeddings_response_queue
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from . schema import triples_request_queue
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from . schema import triples_response_queue
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LABEL="http://www.w3.org/2000/01/rdf-schema#label"
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DEFINITION="http://www.w3.org/2004/02/skos/core#definition"
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class Query:
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def __init__(self, rag, user, collection, verbose):
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self.rag = rag
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self.user = user
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self.collection = collection
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self.verbose = verbose
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def get_vector(self, query):
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if self.verbose:
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print("Compute embeddings...", flush=True)
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qembeds = self.rag.embeddings.request(query)
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if self.verbose:
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print("Done.", flush=True)
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return qembeds
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def get_entities(self, query):
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vectors = self.get_vector(query)
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if self.verbose:
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print("Get entities...", flush=True)
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entities = self.rag.ge_client.request(
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user=self.user, collection=self.collection,
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vectors=vectors, limit=self.rag.entity_limit,
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)
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entities = [
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e.value
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for e in entities
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]
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if self.verbose:
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print("Entities:", flush=True)
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for ent in entities:
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print(" ", ent, flush=True)
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return entities
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def maybe_label(self, e):
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if e in self.rag.label_cache:
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return self.rag.label_cache[e]
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res = self.rag.triples_client.request(
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user=self.user, collection=self.collection,
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s=e, p=LABEL, o=None, limit=1,
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)
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if len(res) == 0:
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self.rag.label_cache[e] = e
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return e
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self.rag.label_cache[e] = res[0].o.value
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return self.rag.label_cache[e]
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def get_subgraph(self, query):
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entities = self.get_entities(query)
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subgraph = set()
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if self.verbose:
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print("Get subgraph...", flush=True)
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for e in entities:
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res = self.rag.triples_client.request(
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user=self.user, collection=self.collection,
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s=e, p=None, o=None,
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limit=self.rag.query_limit
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)
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for triple in res:
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subgraph.add(
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(triple.s.value, triple.p.value, triple.o.value)
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)
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res = self.rag.triples_client.request(
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user=self.user, collection=self.collection,
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s=None, p=e, o=None,
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limit=self.rag.query_limit
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)
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for triple in res:
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subgraph.add(
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(triple.s.value, triple.p.value, triple.o.value)
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)
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res = self.rag.triples_client.request(
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user=self.user, collection=self.collection,
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s=None, p=None, o=e,
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limit=self.rag.query_limit,
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)
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for triple in res:
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subgraph.add(
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(triple.s.value, triple.p.value, triple.o.value)
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)
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subgraph = list(subgraph)
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subgraph = subgraph[0:self.rag.max_subgraph_size]
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if self.verbose:
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print("Subgraph:", flush=True)
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for edge in subgraph:
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print(" ", str(edge), flush=True)
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if self.verbose:
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print("Done.", flush=True)
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return subgraph
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def get_labelgraph(self, query):
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subgraph = self.get_subgraph(query)
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sg2 = []
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for edge in subgraph:
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if edge[1] == LABEL:
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continue
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s = self.maybe_label(edge[0])
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p = self.maybe_label(edge[1])
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o = self.maybe_label(edge[2])
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sg2.append((s, p, o))
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return sg2
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class GraphRag:
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def __init__(
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self,
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pulsar_host="pulsar://pulsar:6650",
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pr_request_queue=None,
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pr_response_queue=None,
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emb_request_queue=None,
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emb_response_queue=None,
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ge_request_queue=None,
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ge_response_queue=None,
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tpl_request_queue=None,
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tpl_response_queue=None,
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verbose=False,
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entity_limit=50,
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triple_limit=30,
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max_subgraph_size=3000,
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module="test",
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):
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self.verbose=verbose
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if pr_request_queue is None:
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pr_request_queue = prompt_request_queue
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if pr_response_queue is None:
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pr_response_queue = prompt_response_queue
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if emb_request_queue is None:
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emb_request_queue = embeddings_request_queue
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if emb_response_queue is None:
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emb_response_queue = embeddings_response_queue
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if ge_request_queue is None:
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ge_request_queue = graph_embeddings_request_queue
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if ge_response_queue is None:
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ge_response_queue = graph_embeddings_response_queue
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if tpl_request_queue is None:
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tpl_request_queue = triples_request_queue
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if tpl_response_queue is None:
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tpl_response_queue = triples_response_queue
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if self.verbose:
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print("Initialising...", flush=True)
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self.ge_client = GraphEmbeddingsClient(
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pulsar_host=pulsar_host,
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subscriber=module + "-ge",
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input_queue=ge_request_queue,
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output_queue=ge_response_queue,
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)
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self.triples_client = TriplesQueryClient(
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pulsar_host=pulsar_host,
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subscriber=module + "-tpl",
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input_queue=tpl_request_queue,
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output_queue=tpl_response_queue
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)
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self.embeddings = EmbeddingsClient(
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pulsar_host=pulsar_host,
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input_queue=emb_request_queue,
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output_queue=emb_response_queue,
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subscriber=module + "-emb",
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)
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self.entity_limit=entity_limit
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self.query_limit=triple_limit
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self.max_subgraph_size=max_subgraph_size
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self.label_cache = {}
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self.prompt = PromptClient(
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pulsar_host=pulsar_host,
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input_queue=pr_request_queue,
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output_queue=pr_response_queue,
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subscriber=module + "-prompt",
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)
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if self.verbose:
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print("Initialised", flush=True)
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def query(self, query, user="trustgraph", collection="default"):
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if self.verbose:
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print("Construct prompt...", flush=True)
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q = Query(
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rag=self, user=user, collection=collection, verbose=self.verbose
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)
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kg = q.get_labelgraph(query)
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if self.verbose:
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print("Invoke LLM...", flush=True)
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print(kg)
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print(query)
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resp = self.prompt.request_kg_prompt(query, kg)
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if self.verbose:
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print("Done", flush=True)
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return resp
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