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🔀 refactor(loading.py): use dictionary to initialize vector stores

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The `instantiate_vectorstore` function now uses a dictionary to initialize vector stores instead of a series of if-else statements. This improves the readability and maintainability of the code. A new dictionary `vecstore_initializer` is added to `vector_store.py` to map the class names of vector stores to their respective initialization functions.
This commit is contained in:
Gabriel Luiz Freitas Almeida 2023-06-23 14:32:15 -03:00
commit 99121d95c1
2 changed files with 20 additions and 31 deletions
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33
src/backend/langflow/interface/initialize/loading.py
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@ -6,15 +6,8 @@ from langchain.agents import agent as agent_module
from langchain.agents.agent import AgentExecutor
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.agents.tools import BaseTool
from langflow.interface.initialize.vector_store import (
initialize_chroma,
initialize_faiss,
initialize_mongodb,
initialize_pinecone,
initialize_qdrant,
initialize_supabase,
initialize_weaviate,
)
from langflow.interface.initialize.vector_store import vecstore_initializer
from pydantic import ValidationError
from langflow.interface.custom_lists import CUSTOM_NODES
@ -151,29 +144,11 @@ def instantiate_embedding(class_object, params):
def instantiate_vectorstore(class_object, params):
search_kwargs = params.pop("search_kwargs", {})
# could be documents or texts
if class_object.__name__ == "Pinecone":
vecstore = initialize_pinecone(class_object, params)
# Chroma requires all metadata values to not be None
elif class_object.__name__ == "Chroma":
vecstore = initialize_chroma(class_object, params)
elif class_object.__name__ == "Qdrant":
vecstore = initialize_qdrant(class_object, params)
elif class_object.__name__ == "Weaviate":
vecstore = initialize_weaviate(class_object, params)
elif class_object.__name__ == "FAISS":
vecstore = initialize_faiss(class_object, params)
elif class_object.__name__ == "SupabaseVectorStore":
vecstore = initialize_supabase(class_object, params)
elif class_object.__name__ == "MongoDBAtlasVectorSearch":
vecstore = initialize_mongodb(class_object, params)
if initializer := vecstore_initializer.get(class_object.__name__):
vecstore = initializer(class_object, params)
else:
if "texts" in params:
params["documents"] = params.pop("texts")
vecstore = class_object.from_documents(**params)
# ! This might not work. Need to test