src/build_vector_db.py

from data_loader import load_documents
from preprocess import clean_text
from embedder import embed_documents
from vector_store import build_faiss_index, save_index


dataset_path = "data/20_newsgroups"

print("Loading dataset...")
docs, labels = load_documents(dataset_path)

print("Cleaning documents...")
docs = [clean_text(d) for d in docs]

print("Generating embeddings...")
embeddings = embed_documents(docs)

print("Building FAISS index...")
index = build_faiss_index(embeddings)

print("Saving FAISS index...")
save_index(index)

print("FAISS index saved in models/")