Update app.py

app.py

@@ -1,9 +1,15 @@
 from haystack.nodes import TextConverter, PDFToTextConverter, DocxToTextConverter, PreProcessor
 import gradio as gr
+from haystack.nodes import PreProcessor
+from haystack.document_stores.faiss import FAISSDocumentStore
+from haystack.nodes import DensePassageRetriever
+from haystack.nodes import FARMReader
+from haystack.pipelines import ExtractiveQAPipeline
+
 pdf_converter = PDFToTextConverter(remove_numeric_tables=True, valid_languages=["en"])
 converted = pdf_converter.convert(file_path="statistics-for-machine-learning.pdf", meta
 
-from haystack.nodes import PreProcessor
+
 preprocessor = PreProcessor(
  split_by="word",
  split_length=200,
@@ -11,19 +17,16 @@ preprocessor = PreProcessor(
  )
 preprocessed = preprocessor.process(converted)   
 
-from haystack.document_stores.faiss import FAISSDocumentStore
 
 document_store = FAISSDocumentStore(faiss_index_factory_str="Flat", return_embedding=True)
 document_store.delete_all_documents()
 document_store.write_documents(preprocessed)
 
-from haystack.nodes import DensePassageRetriever
-from haystack.nodes import FARMReader
+
 retriever = DensePassageRetriever(document_store=document_store)
 reader = FARMReader(model_name_or_path='deepset/roberta-base-squad2-distilled', use_gpu=False)
 document_store.update_embeddings(retriever)
 
-from haystack.pipelines import ExtractiveQAPipeline
 pipeline = ExtractiveQAPipeline(reader, retriever)
 
 questions = [ 'What is linear regression?',