requirements

app.py

@@ -91,6 +91,7 @@ if st.button("Get Answer"):
         repetition_penalty=1.1,
         return_full_text=False,
         max_new_tokens=500,
+        token = os.getenv("HF_TOKEN")
     )
     RERANKER = RAGPretrainedModel.from_pretrained(RERANKER_MODEL_NAME)
     num_doc_before_rerank=15

src/generator.py

@@ -4,6 +4,7 @@ from src.retriever import init_vectorDB_from_doc, retriever
 from transformers import AutoTokenizer, pipeline
 from typing import List,Optional, Tuple # import the Tuple type
 from langchain.docstore.document import Document as LangchainDocument
+from langchain_community.vectorstores import FAISS
 def promt_template(query: str,READER_MODEL_NAME:str,context:str):
     prompt_in_chat_format = [
         {