VECTOR INDEX & Langchain, from_existing_graph

General
,
1

Hello,

I'm trying to understand how 'retrieval_query' parameter in Langchain, from_existing_graph works.
So, when I create vector index with syntax like:

CREATE VECTOR INDEX `abstract-embeddings`
FOR (n: Abstract) ON (n.embedding)
OPTIONS {indexConfig: {
 `vector.dimensions`: 1536,
 `vector.similarity_function`: 'cosine'
}}

I create index for ALL 'Abstract' node properties, right? This happens also when I execute 'from_existing_graph' for the first time, right?
Example:

existing_graph = Neo4jVector.from_existing_graph(
    embedding=OpenAIEmbeddings(),
    url=url,
    username=username,
    password=password,
    index_name="person_index",
    node_label="Person",
    text_node_properties=["name", "location"],
    embedding_node_property="embedding",
)

Parameter 'retrieval_query' should sent some extra chunks of info to the model as I understand - some context. And this looks logical:

read_query = (
    "CALL db.index.vector.queryNodes($index, $k, $embedding) "
    "YIELD node, score "
) + retrieval_query

But when I look at some query example I see:

retrieval_query = """
OPTIONAL MATCH (node)<-[:EDITED_BY]-(p)
WITH node, score, collect(p) AS editors
RETURN node.info AS text,
       score, 
       node {.*, vector: Null, info: Null, editors: editors} AS metadata
"""

So model text is taken from index node not this 'attached' relations or nodes; node.info. I'd expect some info from 'p' nodes. I see nothing is return from 'p' nodes in this query. Am I wrong?

What is 'metadata'? How can I use it in result data?

Thank you for your help