From 5edf819524e25bdbe81e728f305ee1bb11be5843 Mon Sep 17 00:00:00 2001 From: Eugene Yurtsev Date: Mon, 28 Aug 2023 09:30:59 -0400 Subject: [PATCH] Qdrant Client: Expose instance for creating client (#9706) Expose classmethods to convenient initialize the vectostore. The purpose of this PR is to make it easy for users to initialize an empty vectorstore that's properly pre-configured without having to index documents into it via `from_documents`. This will make it easier for users to rely on the following indexing code: https://github.com/langchain-ai/langchain/pull/9614 to help manage data in the qdrant vectorstore. --- libs/langchain/langchain/vectorstores/qdrant.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/libs/langchain/langchain/vectorstores/qdrant.py b/libs/langchain/langchain/vectorstores/qdrant.py index cdc5bea8efb..0be0766f311 100644 --- a/libs/langchain/langchain/vectorstores/qdrant.py +++ b/libs/langchain/langchain/vectorstores/qdrant.py @@ -1298,7 +1298,7 @@ class Qdrant(VectorStore): embeddings = OpenAIEmbeddings() qdrant = Qdrant.from_texts(texts, embeddings, "localhost") """ - qdrant = cls._construct_instance( + qdrant = cls.construct_instance( texts, embedding, location, @@ -1474,7 +1474,7 @@ class Qdrant(VectorStore): embeddings = OpenAIEmbeddings() qdrant = await Qdrant.afrom_texts(texts, embeddings, "localhost") """ - qdrant = await cls._aconstruct_instance( + qdrant = await cls.aconstruct_instance( texts, embedding, location, @@ -1510,7 +1510,7 @@ class Qdrant(VectorStore): return qdrant @classmethod - def _construct_instance( + def construct_instance( cls: Type[Qdrant], texts: List[str], embedding: Embeddings, @@ -1676,7 +1676,7 @@ class Qdrant(VectorStore): return qdrant @classmethod - async def _aconstruct_instance( + async def aconstruct_instance( cls: Type[Qdrant], texts: List[str], embedding: Embeddings,