Update app.py

app.py

@@ -1,10 +1,9 @@
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
 from langchain import PromptTemplate
-from langchain.embeddings import HuggingFaceEmbeddings
+from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
 from langchain.chains import RetrievalQA
-from langchain.chains.llm import LLMChain
-from langchain.chains.question_answering import load_qa_chain
+from langchain_core import RunnableSequence
 import gradio as gr
 
 DB_FAISS_PATH = "vectorstores/db_faiss"
@@ -55,9 +54,9 @@ Helpful answer:
 
 def retrieval_QA_chain(llm, prompt, db):
     """
-    Create a RetrievalQA chain with the specified LLM, prompt, and vector store.
+    Create a RetrievalQA chain with the specified LLM, prompt, and vector store using the updated RunnableSequence.
     """
-    llm_chain = LLMChain(llm=llm, prompt=prompt)
+    llm_chain = RunnableSequence([prompt, llm])
     qachain = RetrievalQA.from_chain_type(
         llm_chain=llm_chain,
         chain_type="stuff",