Update app.py

app.py

@@ -32,14 +32,14 @@ pipe = pipeline("text-generation", model = model, tokenizer = tokenizer, max_new
 hf = HuggingFacePipeline(pipeline=pipe)
 
 def document_prep():
-    ## commenting this code because now we are loading vectors directly and not parsing the pdf
+    
     pdfLoader = PyPDFLoader("./LangchainPaper/RAGInputPaper.pdf")
     documents = pdfLoader.load()
    
     text_splitter = RecursiveCharacterTextSplitter(chunk_size = 512, chunk_overlap = 30)
     docs = text_splitter.split_documents(documents)
    
-    creating vector embeddings during run using FAISS
+    # creating vector embeddings during run using FAISS
     vectorstore = FAISS.from_documents(
     docs, embedding=embeddings
     )
@@ -53,6 +53,7 @@ def load_vector():
     return retriever
 
 # call the function from which you want to load the vector
+retriever=document_prep()
 retriever=load_vector()
     
 ## In memory store