from sentence_transformers import SentenceTransformer, util
import openai
with open('HKIHRMEmployeeHandbook.txt') as f:
full_text = f.read()
passages = [line.strip() for line in full_text.split('\n \n') if len(line.strip()) > 0]
model_name = 'multi-qa-mpnet-base-cos-v1'
bi_encoder = SentenceTransformer(model_name)
corpus_embeddings = bi_encoder.encode(passages, convert_to_tensor=True, show_progress_bar=True)