From 9bbdd9465b6fc910d594ecd61d4e623ec7b69f13 Mon Sep 17 00:00:00 2001 From: Gabriel Luiz Freitas Almeida Date: Wed, 9 Aug 2023 15:47:22 -0300 Subject: [PATCH] =?UTF-8?q?=F0=9F=94=A8=20refactor(Vectara.py):=20reorgani?= =?UTF-8?q?ze=20function=20parameters=20for=20better=20readability=20and?= =?UTF-8?q?=20maintainability=20=F0=9F=94=A7=20chore(Vectara.py):=20add=20?= =?UTF-8?q?"embedding"=20parameter=20to=20the=20build=20function=20to=20su?= =?UTF-8?q?pport=20custom=20embeddings=20in=20VectaraComponent?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- src/backend/langflow/components/vectorstores/Vectara.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/src/backend/langflow/components/vectorstores/Vectara.py b/src/backend/langflow/components/vectorstores/Vectara.py index 6092b1b04..6576d146d 100644 --- a/src/backend/langflow/components/vectorstores/Vectara.py +++ b/src/backend/langflow/components/vectorstores/Vectara.py @@ -5,6 +5,7 @@ from langchain.vectorstores import Vectara from langchain.schema import Document from langchain.vectorstores.base import VectorStore from langchain.schema import BaseRetriever +from langchain.embeddings.base import Embeddings class VectaraComponent(CustomComponent): @@ -21,14 +22,16 @@ class VectaraComponent(CustomComponent): "vectara_api_key": {"display_name": "Vectara API Key", "password": True}, "code": {"show": False}, "documents": {"display_name": "Documents"}, + "embedding": {"display_name": "Embedding"}, } def build( self, - documents: Optional[Document], vectara_customer_id: str, vectara_corpus_id: str, vectara_api_key: str, + embedding: Optional[Embeddings] = None, + documents: Optional[Document] = None, ) -> Union[VectorStore, BaseRetriever]: # If documents, then we need to create a Vectara instance using .from_documents if documents: @@ -37,6 +40,7 @@ class VectaraComponent(CustomComponent): vectara_customer_id=vectara_customer_id, vectara_corpus_id=vectara_corpus_id, vectara_api_key=vectara_api_key, + embedding=embedding, ) return Vectara(