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community[neo4j_vector]: make embedding dimension check optional (#25737)

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**Description:**

Starting from Neo4j 5.23 (22 August 2024), with vector-2.0 indexes,
`vector.dimensions` is not required to be set, which will cause it the
key not exist error in index config if it's not set.

Since the existence of vector.dimensions will only ensure additional
checks, this commit turns embedding dimension check optional, and only
do checks when it exists (not None).

https://neo4j.com/release-notes/database/neo4j-5/

**Twitter handle:** @HollowM186

Signed-off-by: Hollow Man <hollowman@opensuse.org>
Co-authored-by: Erick Friis <erick@langchain.dev>
This commit is contained in:
ℍ𝕠𝕝𝕝𝕠𝕨 𝕄𝕒𝕟 2024-08-31 15:36:20 +03:00 committed by GitHub
parent 0a752a74cc
commit 64b62f6ae4
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GPG Key ID: B5690EEEBB952194
1 changed files with 16 additions and 11 deletions
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27
libs/community/langchain_community/vectorstores/neo4j_vector.py
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@ -692,9 +692,10 @@ class Neo4jVector(VectorStore):
self.node_label = index_information[0]["labelsOrTypes"][0]
self.embedding_node_property = index_information[0]["properties"][0]
self._index_type = index_information[0]["entityType"]
embedding_dimension = index_information[0]["options"]["indexConfig"][
"vector.dimensions"
]
embedding_dimension = None
index_config = index_information[0]["options"]["indexConfig"]
if "vector.dimensions" in index_config:
embedding_dimension = index_config["vector.dimensions"]
return embedding_dimension, index_information[0]["entityType"]
except IndexError:
@ -808,10 +809,12 @@ class Neo4jVector(VectorStore):
)
# If the vector index doesn't exist yet
if not embedding_dimension:
if not index_type:
store.create_new_index()
# If the index already exists, check if embedding dimensions match
elif not store.embedding_dimension == embedding_dimension:
elif (
embedding_dimension and not store.embedding_dimension == embedding_dimension
):
raise ValueError(
f"Index with name {store.index_name} already exists."
"The provided embedding function and vector index "
@ -1275,14 +1278,14 @@ class Neo4jVector(VectorStore):
"`from_existing_relationship_index` method."
)
if not embedding_dimension:
if not index_type:
raise ValueError(
"The specified vector index name does not exist. "
"Make sure to check if you spelled it correctly"
)
# Check if embedding function and vector index dimensions match
if not store.embedding_dimension == embedding_dimension:
if embedding_dimension and not store.embedding_dimension == embedding_dimension:
raise ValueError(
"The provided embedding function and vector index "
"dimensions do not match.\n"
@ -1337,7 +1340,7 @@ class Neo4jVector(VectorStore):
embedding_dimension, index_type = store.retrieve_existing_index()
if not embedding_dimension:
if not index_type:
raise ValueError(
"The specified vector index name does not exist. "
"Make sure to check if you spelled it correctly"
@ -1351,7 +1354,7 @@ class Neo4jVector(VectorStore):
)
# Check if embedding function and vector index dimensions match
if not store.embedding_dimension == embedding_dimension:
if embedding_dimension and not store.embedding_dimension == embedding_dimension:
raise ValueError(
"The provided embedding function and vector index "
"dimensions do not match.\n"
@ -1464,10 +1467,12 @@ class Neo4jVector(VectorStore):
)
# If the vector index doesn't exist yet
if not embedding_dimension:
if not index_type:
store.create_new_index()
# If the index already exists, check if embedding dimensions match
elif not store.embedding_dimension == embedding_dimension:
elif (
embedding_dimension and not store.embedding_dimension == embedding_dimension
):
raise ValueError(
f"Index with name {store.index_name} already exists."
"The provided embedding function and vector index "