Neo4jVector, What is the index_name in the method used for?

[nuocheng]

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Example Code

from langchain.graphs import Neo4jGraph
from langchain_community.embeddings import HuggingFaceEmbeddings
graph = Neo4jGraph(
    url=url,
    username=username,
    password=password
)
vector_index = Neo4jVector.from_existing_graph(
    embeddings,
    search_type="hybrid",
    url=url,
    username=username,
    password=password,
    index_name="elementId",
    node_label="table",
    text_node_properties=['name', 'card', 'contrast','echarts','predict'],
    embedding_node_property='embedding',
)


relation_type = Neo4jVector.from_existing_relationship_index(
    embeddings,
    search_type = 'VECTOR',
    url=url,
    username=username,
    password=password,
    index_name="?",
    text_node_property="text",
)

Description

Neo4jVector.from_existing_graph and Neo4jVector.from_existing_relationship_index, what is the index_name in these two methods used for?

System Info

google-ai-generativelanguage 0.4.0
langchain 0.2.0
langchain-community 0.2.1
langchain-core 0.2.0
langchain-experimental 0.0.57
langchain-google-genai 0.0.9
langchain-text-splitters 0.2.0
langsmith 0.1.50
llama-index-embeddings-langchain 0.1.2

[dosubot[bot]]

The index_name parameter in the methods Neo4jVector.from_existing_graph and Neo4jVector.from_existing_relationship_index is used to specify the name of the existing vector index in the Neo4j database that the method should use. This parameter is essential for identifying and interacting with the correct vector index without creating new embeddings ^[1][2].

Details

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[SetonLiang]

What' s the embedding function you invoke while creating the index