Update vector_store.py

vector_store.py

@@ -1,12 +1,12 @@
 import faiss
 from langchain.vectorstores import FAISS
 from langchain.schema import Document
-from embeddings import embedding_model  # Correct the import to directly reference the embeddings.py file
+from embeddings import get_embedding  # Import the updated embedding function
 
-# Initialize FAISS index
-dim = 384  # MiniLM embedding size
+# FAISS parameters
+dim = 384  # Size of the embedding (MiniLM has 384-dimensional vectors)
 index = faiss.IndexFlatL2(dim)
-vector_db = FAISS(embedding_function=embedding_model, index=index)
+vector_db = FAISS(embedding_function=get_embedding, index=index)
 
 def add_document(text, doc_id):
     """Add document embeddings to FAISS."""