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Update Pinecone Upsert method usage (#7358)

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Description: Refactor the upsert method in the Pinecone class to allow
for additional keyword arguments. This change adds flexibility and
extensibility to the method, allowing for future modifications or
enhancements. The upsert method now accepts the `**kwargs` parameter,
which can be used to pass any additional arguments to the Pinecone
index. This change has been made in both the `upsert` method in the
`Pinecone` class and the `upsert` method in the
`similarity_search_with_score` class method. Falls in line with the
usage of the upsert method in
[Pinecone-Python-Client](4640c4cf27/pinecone/index.py (L73))
Issue: [This feature request in Pinecone
Repo](https://github.com/pinecone-io/pinecone-python-client/issues/184)

Maintainer responsibilities:
  - General / Misc / if you don't know who to tag: @baskaryan
  - Memory: @hwchase17

---------

Co-authored-by: kwesi <22204443+yankskwesi@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Lance Martin <122662504+rlancemartin@users.noreply.github.com>
This commit is contained in:
Pharbie 2023-07-11 21:14:42 -04:00 committed by GitHub
parent 5c3fe8b0d1
commit 74c28df363
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1 changed files with 7 additions and 3 deletions
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10
langchain/vectorstores/pinecone.py
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@ -94,7 +94,9 @@ class Pinecone(VectorStore):
metadata[self._text_key] = text
docs.append((ids[i], embedding, metadata))
# upsert to Pinecone
self._index.upsert(vectors=docs, namespace=namespace, batch_size=batch_size)
self._index.upsert(
vectors=docs, namespace=namespace, batch_size=batch_size, **kwargs
)
return ids
def similarity_search_with_score(
@ -274,6 +276,7 @@ class Pinecone(VectorStore):
text_key: str = "text",
index_name: Optional[str] = None,
namespace: Optional[str] = None,
upsert_kwargs: Optional[dict] = None,
**kwargs: Any,
) -> Pinecone:
"""Construct Pinecone wrapper from raw documents.
@ -346,8 +349,9 @@ class Pinecone(VectorStore):
to_upsert = zip(ids_batch, embeds, metadata)
# upsert to Pinecone
index.upsert(vectors=list(to_upsert), namespace=namespace)
return cls(index, embedding.embed_query, text_key, namespace)
_upsert_kwargs = upsert_kwargs or {}
index.upsert(vectors=list(to_upsert), namespace=namespace, **_upsert_kwargs)
return cls(index, embedding.embed_query, text_key, namespace, **kwargs)
@classmethod
def from_existing_index(