src/indexing/vectore_store.py

from langchain_community.vectorstores import SKLearnVectorStore
from langchain_community.embeddings.fastembed import FastEmbedEmbeddings

class VectorStoreManager:
    def __init__(self, embedding_model="BAAI/bge-base-en-v1.5"):
        self.embeddings = FastEmbedEmbeddings(model_name=embedding_model)
        
    def create_vector_store(self):
        """Create a new vector store"""
        vector_store = SKLearnVectorStore(
            metric="cosine",
            embedding=self.embeddings,
        )
 
        return vector_store
    
    def index_documents(self, documents):
        """Index documents into vector store"""
        vector_store = self.create_vector_store()
        vector_store.add_documents(documents=documents)
        return vector_store