Update app.py

app.py

@@ -20,8 +20,8 @@ from langchain import PromptTemplate, LLMChain
 # Vector stores
 from langchain.vectorstores import FAISS
 
-# Models
-from langchain.llms import HuggingFacePipeline
+# Import HuggingFacePipeline from the new package
+from langchain_huggingface import HuggingFacePipeline
 from langchain.embeddings import HuggingFaceInstructEmbeddings
 
 # Retrievers
@@ -43,7 +43,7 @@ shutil.rmtree('./.cache', ignore_errors=True)
 
 class CFG:
     # LLMs configuration
-    model_name = 'llama2-13b-chat'  # Options: wizardlm, llama2-7b-chat, llama2-13b-chat, mistral-7B
+    model_name = 'llama2-13b-chat'
     temperature = 0
     top_p = 0.95
     repetition_penalty = 1.15
@@ -130,14 +130,13 @@ pipe = pipeline(
     repetition_penalty=CFG.repetition_penalty
 )
 
-# LangChain pipeline setup
+# Use the updated HuggingFacePipeline class from langchain_huggingface
 llm = HuggingFacePipeline(pipeline=pipe)
 
 loader = DirectoryLoader(
     CFG.PDFs_path,
     glob="./*.pdf",
     loader_cls=PyPDFLoader,
-    show_progress=True,
 )
 
 documents = loader.load()
@@ -160,8 +159,7 @@ retriever = vectordb.as_retriever(search_kwargs={"k": CFG.k})
 
 qa_chain = RetrievalQA.from_chain_type(
     llm=llm,
-    chain_type="stuff",  # Options: map_reduce, map_rerank, stuff, refine
-    retriever=retriever,
+    chain_type="stuff",
 )
 
 prompt_template = """