Update langchain_helper.py

langchain_helper.py

@@ -1,7 +1,7 @@
 from langchain.vectorstores import FAISS
 from langchain.llms import GooglePalm
 from langchain.document_loaders.csv_loader import CSVLoader
-from langchain.embeddings import HuggingFaceInstructEmbeddings
+from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain.prompts import PromptTemplate
 from langchain.chains import RetrievalQA
 import os
@@ -12,7 +12,7 @@ load_dotenv()  # take environment variables from .env (especially openai api key
 # Create Google Palm LLM model
 llm = GooglePalm(google_api_key=os.environ["GOOGLE_API_KEY"], temperature=0.1)
 # # Initialize instructor embeddings using the Hugging Face model
-instructor_embeddings = HuggingFaceInstructEmbeddings(model_name="hkunlp/instructor-large")
+instructor_embeddings = HuggingFaceEmbeddings(model_name="hkunlp/instructor-large")
 vectordb_file_path = "faiss_index"
 
 def create_vector_db():