import streamlit as st
from haystack.utils import fetch_archive_from_http, clean_wiki_text, convert_files_to_docs
from haystack.schema import Answer
from haystack.document_stores import InMemoryDocumentStore
from haystack.pipelines import ExtractiveQAPipeline
from haystack.nodes import FARMReader, TfidfRetriever
import validators
import json

#Haystack Components
document_store = InMemoryDocumentStore()
retriever = TfidfRetriever(document_store=document_store)
reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2", use_gpu=True)
pipeline = ExtractiveQAPipeline(reader, retriever)

def load_and_write_data():
    doc_dir = './article_txt_got'
    docs = convert_files_to_docs(dir_path=doc_dir, clean_func=clean_wiki_text, split_paragraphs=True)

    document_store.write_documents(docs)

#Streamlit App

st.title('Game of Thrones QA with Haystack')
question = st.text_input(label="Ask a Question about Game of Thromes", value="Who is Arya's father?")

load_and_write_data()

def ask_question(question):
    prediction = pipeline.run(query=question, params={"Retriever": {"top_k": 10}, "Reader": {"top_k": 5}})
    st.write(Answer(prediction['answers'][0]).to_dict())
    st.write(Answer(prediction['answers'][1]).to_dict())
    st.write(Answer(prediction['answers'][2]).to_dict())

if question:
    ask_question(question)