first commit
This commit is contained in:
512
graphs/neptune/neptunedb.py
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512
graphs/neptune/neptunedb.py
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import logging
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import uuid
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from datetime import datetime
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import pytz
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from .base import NeptuneBase
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try:
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from langchain_aws import NeptuneGraph
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except ImportError:
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raise ImportError("langchain_aws is not installed. Please install it using 'make install_all'.")
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logger = logging.getLogger(__name__)
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class MemoryGraph(NeptuneBase):
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def __init__(self, config):
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"""
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Initialize the Neptune DB memory store.
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"""
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self.config = config
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self.graph = None
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endpoint = self.config.graph_store.config.endpoint
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if endpoint and endpoint.startswith("neptune-db://"):
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host = endpoint.replace("neptune-db://", "")
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port = 8182
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self.graph = NeptuneGraph(host, port)
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if not self.graph:
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raise ValueError("Unable to create a Neptune-DB client: missing 'endpoint' in config")
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self.node_label = ":`__Entity__`" if self.config.graph_store.config.base_label else ""
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self.embedding_model = NeptuneBase._create_embedding_model(self.config)
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# Default to openai if no specific provider is configured
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self.llm_provider = "openai"
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if self.config.graph_store.llm:
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self.llm_provider = self.config.graph_store.llm.provider
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elif self.config.llm.provider:
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self.llm_provider = self.config.llm.provider
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# fetch the vector store as a provider
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self.vector_store_provider = self.config.vector_store.provider
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if self.config.graph_store.config.collection_name:
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vector_store_collection_name = self.config.graph_store.config.collection_name
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else:
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vector_store_config = self.config.vector_store.config
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if vector_store_config.collection_name:
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vector_store_collection_name = vector_store_config.collection_name + "_neptune_vector_store"
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else:
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vector_store_collection_name = "mem0_neptune_vector_store"
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self.config.vector_store.config.collection_name = vector_store_collection_name
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self.vector_store = NeptuneBase._create_vector_store(self.vector_store_provider, self.config)
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self.llm = NeptuneBase._create_llm(self.config, self.llm_provider)
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self.user_id = None
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# Use threshold from graph_store config, default to 0.7 for backward compatibility
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self.threshold = self.config.graph_store.threshold if hasattr(self.config.graph_store, 'threshold') else 0.7
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self.vector_store_limit=5
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def _delete_entities_cypher(self, source, destination, relationship, user_id):
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"""
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Returns the OpenCypher query and parameters for deleting entities in the graph DB
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:param source: source node
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:param destination: destination node
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:param relationship: relationship label
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:param user_id: user_id to use
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:return: str, dict
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"""
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cypher = f"""
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MATCH (n {self.node_label} {{name: $source_name, user_id: $user_id}})
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-[r:{relationship}]->
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(m {self.node_label} {{name: $dest_name, user_id: $user_id}})
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DELETE r
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RETURN
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n.name AS source,
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m.name AS target,
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type(r) AS relationship
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"""
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params = {
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"source_name": source,
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"dest_name": destination,
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"user_id": user_id,
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}
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logger.debug(f"_delete_entities\n query={cypher}")
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return cypher, params
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def _add_entities_by_source_cypher(
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self,
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source_node_list,
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destination,
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dest_embedding,
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destination_type,
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relationship,
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user_id,
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):
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"""
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Returns the OpenCypher query and parameters for adding entities in the graph DB
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:param source_node_list: list of source nodes
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:param destination: destination name
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:param dest_embedding: destination embedding
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:param destination_type: destination node label
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:param relationship: relationship label
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:param user_id: user id to use
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:return: str, dict
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"""
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destination_id = str(uuid.uuid4())
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destination_payload = {
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"name": destination,
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"type": destination_type,
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"user_id": user_id,
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"created_at": datetime.now(pytz.timezone("US/Pacific")).isoformat(),
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}
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self.vector_store.insert(
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vectors=[dest_embedding],
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payloads=[destination_payload],
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ids=[destination_id],
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)
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destination_label = self.node_label if self.node_label else f":`{destination_type}`"
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destination_extra_set = f", destination:`{destination_type}`" if self.node_label else ""
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cypher = f"""
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MATCH (source {{user_id: $user_id}})
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WHERE id(source) = $source_id
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SET source.mentions = coalesce(source.mentions, 0) + 1
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WITH source
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MERGE (destination {destination_label} {{`~id`: $destination_id, name: $destination_name, user_id: $user_id}})
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ON CREATE SET
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destination.created = timestamp(),
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destination.updated = timestamp(),
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destination.mentions = 1
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{destination_extra_set}
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ON MATCH SET
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destination.mentions = coalesce(destination.mentions, 0) + 1,
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destination.updated = timestamp()
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WITH source, destination
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MERGE (source)-[r:{relationship}]->(destination)
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ON CREATE SET
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r.created = timestamp(),
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r.updated = timestamp(),
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r.mentions = 1
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ON MATCH SET
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r.mentions = coalesce(r.mentions, 0) + 1,
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r.updated = timestamp()
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RETURN source.name AS source, type(r) AS relationship, destination.name AS target, id(destination) AS destination_id
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"""
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params = {
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"source_id": source_node_list[0]["id(source_candidate)"],
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"destination_id": destination_id,
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"destination_name": destination,
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"dest_embedding": dest_embedding,
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"user_id": user_id,
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}
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logger.debug(
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f"_add_entities:\n source_node_search_result={source_node_list[0]}\n query={cypher}"
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)
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return cypher, params
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def _add_entities_by_destination_cypher(
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self,
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source,
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source_embedding,
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source_type,
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destination_node_list,
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relationship,
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user_id,
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):
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"""
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Returns the OpenCypher query and parameters for adding entities in the graph DB
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:param source: source node name
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:param source_embedding: source node embedding
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:param source_type: source node label
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:param destination_node_list: list of dest nodes
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:param relationship: relationship label
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:param user_id: user id to use
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:return: str, dict
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"""
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source_id = str(uuid.uuid4())
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source_payload = {
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"name": source,
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"type": source_type,
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"user_id": user_id,
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"created_at": datetime.now(pytz.timezone("US/Pacific")).isoformat(),
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}
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self.vector_store.insert(
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vectors=[source_embedding],
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payloads=[source_payload],
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ids=[source_id],
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)
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source_label = self.node_label if self.node_label else f":`{source_type}`"
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source_extra_set = f", source:`{source_type}`" if self.node_label else ""
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cypher = f"""
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MATCH (destination {{user_id: $user_id}})
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WHERE id(destination) = $destination_id
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SET
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destination.mentions = coalesce(destination.mentions, 0) + 1,
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destination.updated = timestamp()
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WITH destination
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MERGE (source {source_label} {{`~id`: $source_id, name: $source_name, user_id: $user_id}})
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ON CREATE SET
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source.created = timestamp(),
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source.updated = timestamp(),
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source.mentions = 1
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{source_extra_set}
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ON MATCH SET
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source.mentions = coalesce(source.mentions, 0) + 1,
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source.updated = timestamp()
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WITH source, destination
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MERGE (source)-[r:{relationship}]->(destination)
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ON CREATE SET
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r.created = timestamp(),
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r.updated = timestamp(),
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r.mentions = 1
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ON MATCH SET
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r.mentions = coalesce(r.mentions, 0) + 1,
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r.updated = timestamp()
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RETURN source.name AS source, type(r) AS relationship, destination.name AS target
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"""
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params = {
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"destination_id": destination_node_list[0]["id(destination_candidate)"],
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"source_id": source_id,
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"source_name": source,
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"source_embedding": source_embedding,
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"user_id": user_id,
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}
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logger.debug(
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f"_add_entities:\n destination_node_search_result={destination_node_list[0]}\n query={cypher}"
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)
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return cypher, params
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def _add_relationship_entities_cypher(
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self,
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source_node_list,
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destination_node_list,
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relationship,
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user_id,
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):
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"""
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Returns the OpenCypher query and parameters for adding entities in the graph DB
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:param source_node_list: list of source node ids
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:param destination_node_list: list of dest node ids
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:param relationship: relationship label
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:param user_id: user id to use
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:return: str, dict
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"""
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cypher = f"""
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MATCH (source {{user_id: $user_id}})
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WHERE id(source) = $source_id
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SET
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source.mentions = coalesce(source.mentions, 0) + 1,
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source.updated = timestamp()
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WITH source
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MATCH (destination {{user_id: $user_id}})
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WHERE id(destination) = $destination_id
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SET
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destination.mentions = coalesce(destination.mentions) + 1,
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destination.updated = timestamp()
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MERGE (source)-[r:{relationship}]->(destination)
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ON CREATE SET
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r.created_at = timestamp(),
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r.updated_at = timestamp(),
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r.mentions = 1
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ON MATCH SET r.mentions = coalesce(r.mentions, 0) + 1
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RETURN source.name AS source, type(r) AS relationship, destination.name AS target
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"""
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params = {
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"source_id": source_node_list[0]["id(source_candidate)"],
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"destination_id": destination_node_list[0]["id(destination_candidate)"],
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"user_id": user_id,
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}
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logger.debug(
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f"_add_entities:\n destination_node_search_result={destination_node_list[0]}\n source_node_search_result={source_node_list[0]}\n query={cypher}"
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)
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return cypher, params
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def _add_new_entities_cypher(
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self,
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source,
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source_embedding,
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source_type,
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destination,
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dest_embedding,
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destination_type,
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relationship,
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user_id,
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):
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"""
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Returns the OpenCypher query and parameters for adding entities in the graph DB
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:param source: source node name
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:param source_embedding: source node embedding
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:param source_type: source node label
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:param destination: destination name
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:param dest_embedding: destination embedding
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:param destination_type: destination node label
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:param relationship: relationship label
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:param user_id: user id to use
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:return: str, dict
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"""
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source_id = str(uuid.uuid4())
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source_payload = {
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"name": source,
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"type": source_type,
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"user_id": user_id,
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"created_at": datetime.now(pytz.timezone("US/Pacific")).isoformat(),
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}
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destination_id = str(uuid.uuid4())
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destination_payload = {
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"name": destination,
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"type": destination_type,
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"user_id": user_id,
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"created_at": datetime.now(pytz.timezone("US/Pacific")).isoformat(),
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}
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self.vector_store.insert(
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vectors=[source_embedding, dest_embedding],
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payloads=[source_payload, destination_payload],
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ids=[source_id, destination_id],
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)
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source_label = self.node_label if self.node_label else f":`{source_type}`"
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source_extra_set = f", source:`{source_type}`" if self.node_label else ""
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destination_label = self.node_label if self.node_label else f":`{destination_type}`"
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destination_extra_set = f", destination:`{destination_type}`" if self.node_label else ""
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cypher = f"""
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MERGE (n {source_label} {{name: $source_name, user_id: $user_id, `~id`: $source_id}})
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ON CREATE SET n.created = timestamp(),
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n.mentions = 1
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{source_extra_set}
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ON MATCH SET n.mentions = coalesce(n.mentions, 0) + 1
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WITH n
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MERGE (m {destination_label} {{name: $dest_name, user_id: $user_id, `~id`: $dest_id}})
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ON CREATE SET m.created = timestamp(),
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m.mentions = 1
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{destination_extra_set}
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ON MATCH SET m.mentions = coalesce(m.mentions, 0) + 1
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WITH n, m
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MERGE (n)-[rel:{relationship}]->(m)
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ON CREATE SET rel.created = timestamp(), rel.mentions = 1
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ON MATCH SET rel.mentions = coalesce(rel.mentions, 0) + 1
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RETURN n.name AS source, type(rel) AS relationship, m.name AS target
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"""
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params = {
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"source_id": source_id,
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"dest_id": destination_id,
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"source_name": source,
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"dest_name": destination,
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"source_embedding": source_embedding,
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"dest_embedding": dest_embedding,
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"user_id": user_id,
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}
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logger.debug(
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f"_add_new_entities_cypher:\n query={cypher}"
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)
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return cypher, params
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def _search_source_node_cypher(self, source_embedding, user_id, threshold):
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"""
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Returns the OpenCypher query and parameters to search for source nodes
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:param source_embedding: source vector
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:param user_id: user_id to use
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:param threshold: the threshold for similarity
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:return: str, dict
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"""
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source_nodes = self.vector_store.search(
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query="",
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vectors=source_embedding,
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limit=self.vector_store_limit,
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filters={"user_id": user_id},
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)
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ids = [n.id for n in filter(lambda s: s.score > threshold, source_nodes)]
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cypher = f"""
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MATCH (source_candidate {self.node_label})
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WHERE source_candidate.user_id = $user_id AND id(source_candidate) IN $ids
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RETURN id(source_candidate)
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"""
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params = {
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"ids": ids,
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"source_embedding": source_embedding,
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"user_id": user_id,
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"threshold": threshold,
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}
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logger.debug(f"_search_source_node\n query={cypher}")
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return cypher, params
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def _search_destination_node_cypher(self, destination_embedding, user_id, threshold):
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"""
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Returns the OpenCypher query and parameters to search for destination nodes
|
||||
|
||||
:param source_embedding: source vector
|
||||
:param user_id: user_id to use
|
||||
:param threshold: the threshold for similarity
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||||
:return: str, dict
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||||
"""
|
||||
destination_nodes = self.vector_store.search(
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query="",
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vectors=destination_embedding,
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limit=self.vector_store_limit,
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filters={"user_id": user_id},
|
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)
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ids = [n.id for n in filter(lambda d: d.score > threshold, destination_nodes)]
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cypher = f"""
|
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MATCH (destination_candidate {self.node_label})
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WHERE destination_candidate.user_id = $user_id AND id(destination_candidate) IN $ids
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RETURN id(destination_candidate)
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||||
"""
|
||||
|
||||
params = {
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"ids": ids,
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"destination_embedding": destination_embedding,
|
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"user_id": user_id,
|
||||
}
|
||||
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||||
logger.debug(f"_search_destination_node\n query={cypher}")
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return cypher, params
|
||||
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||||
def _delete_all_cypher(self, filters):
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||||
"""
|
||||
Returns the OpenCypher query and parameters to delete all edges/nodes in the memory store
|
||||
|
||||
:param filters: search filters
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||||
:return: str, dict
|
||||
"""
|
||||
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||||
# remove the vector store index
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||||
self.vector_store.reset()
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||||
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||||
# create a query that: deletes the nodes of the graph_store
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cypher = f"""
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MATCH (n {self.node_label} {{user_id: $user_id}})
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DETACH DELETE n
|
||||
"""
|
||||
params = {"user_id": filters["user_id"]}
|
||||
|
||||
logger.debug(f"delete_all query={cypher}")
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||||
return cypher, params
|
||||
|
||||
def _get_all_cypher(self, filters, limit):
|
||||
"""
|
||||
Returns the OpenCypher query and parameters to get all edges/nodes in the memory store
|
||||
|
||||
:param filters: search filters
|
||||
:param limit: return limit
|
||||
:return: str, dict
|
||||
"""
|
||||
|
||||
cypher = f"""
|
||||
MATCH (n {self.node_label} {{user_id: $user_id}})-[r]->(m {self.node_label} {{user_id: $user_id}})
|
||||
RETURN n.name AS source, type(r) AS relationship, m.name AS target
|
||||
LIMIT $limit
|
||||
"""
|
||||
params = {"user_id": filters["user_id"], "limit": limit}
|
||||
return cypher, params
|
||||
|
||||
def _search_graph_db_cypher(self, n_embedding, filters, limit):
|
||||
"""
|
||||
Returns the OpenCypher query and parameters to search for similar nodes in the memory store
|
||||
|
||||
:param n_embedding: node vector
|
||||
:param filters: search filters
|
||||
:param limit: return limit
|
||||
:return: str, dict
|
||||
"""
|
||||
|
||||
# search vector store for applicable nodes using cosine similarity
|
||||
search_nodes = self.vector_store.search(
|
||||
query="",
|
||||
vectors=n_embedding,
|
||||
limit=self.vector_store_limit,
|
||||
filters=filters,
|
||||
)
|
||||
|
||||
ids = [n.id for n in search_nodes]
|
||||
|
||||
cypher_query = f"""
|
||||
MATCH (n {self.node_label})-[r]->(m)
|
||||
WHERE n.user_id = $user_id AND id(n) IN $n_ids
|
||||
RETURN n.name AS source, id(n) AS source_id, type(r) AS relationship, id(r) AS relation_id, m.name AS destination, id(m) AS destination_id
|
||||
UNION
|
||||
MATCH (m)-[r]->(n {self.node_label})
|
||||
RETURN m.name AS source, id(m) AS source_id, type(r) AS relationship, id(r) AS relation_id, n.name AS destination, id(n) AS destination_id
|
||||
LIMIT $limit
|
||||
"""
|
||||
params = {
|
||||
"n_ids": ids,
|
||||
"user_id": filters["user_id"],
|
||||
"limit": limit,
|
||||
}
|
||||
logger.debug(f"_search_graph_db\n query={cypher_query}")
|
||||
|
||||
return cypher_query, params
|
||||
Reference in New Issue
Block a user