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import os | |
import time | |
import streamlit as st | |
import subprocess | |
import sys | |
import logging | |
import pandas as pd | |
from json import JSONDecodeError | |
from pathlib import Path | |
from markdown import markdown | |
import random | |
from typing import List, Dict, Any, Tuple | |
from haystack.document_stores import ElasticsearchDocumentStore, FAISSDocumentStore | |
from haystack.nodes import EmbeddingRetriever | |
from haystack.pipelines import ExtractiveQAPipeline | |
from haystack.preprocessor.preprocessor import PreProcessor | |
from haystack.nodes import FARMReader, TransformersReader | |
from haystack.pipelines import ExtractiveQAPipeline | |
from annotated_text import annotation | |
import shutil | |
# FAISS index directory | |
INDEX_DIR = 'data/index' | |
# the following function is cached to make index and models load only at start | |
def start_haystack(): | |
""" | |
load document store, retriever, reader and create pipeline | |
""" | |
shutil.copy(f'{INDEX_DIR}/faiss_document_store.db','.') | |
document_store = FAISSDocumentStore( | |
faiss_index_path=f'{INDEX_DIR}/my_faiss_index.faiss', | |
faiss_config_path=f'{INDEX_DIR}/my_faiss_index.json') | |
print (f'Index size: {document_store.get_document_count()}') | |
retriever = EmbeddingRetriever( | |
document_store=document_store, | |
embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1", | |
model_format="sentence_transformers" | |
) | |
reader = FARMReader(model_name_or_path="deepset/roberta-base-squad2", use_gpu=True) | |
pipe = ExtractiveQAPipeline(reader, retriever) | |
return pipe | |
def set_state_if_absent(key, value): | |
if key not in st.session_state: | |
st.session_state[key] = value | |
def get_backlink(result, ip) -> str: | |
""" | |
Build URL from metadata and Google VM IP | |
(quick and dirty) | |
""" | |
meta = result['meta'] | |
fpath = meta['filepath'].rpartition('/')[-1] | |
fname = fpath.rpartition('.')[0] | |
return f'http://{ip}:8000/data/final/ner_html/{fname}.html' | |
def query(pipe, question): | |
"""Run query and get answers""" | |
return (pipe.run(question, params={"Retriever": {"top_k": 10}, "Reader": {"top_k": 5}}), None) | |
def main(): | |
# st.set_page_config(page_title='Who killed Laura Palmer?', | |
# page_icon="https://static.wikia.nocookie.net/twinpeaks/images/4/4a/Site-favicon.ico/revision/latest?cb=20210710003705") | |
pipe=start_haystack() | |
# my_ip=subprocess.run(['curl', 'ifconfig.me'], stdout=subprocess.PIPE).stdout.decode('utf-8') | |
# Persistent state | |
set_state_if_absent('question', "Where is Twin Peaks?") | |
set_state_if_absent('answer', '') | |
set_state_if_absent('results', None) | |
set_state_if_absent('raw_json', None) | |
set_state_if_absent('random_question_requested', False) | |
# Small callback to reset the interface in case the text of the question changes | |
def reset_results(*args): | |
st.session_state.answer = None | |
st.session_state.results = None | |
st.session_state.raw_json = None | |
# Title | |
st.write("# Who killed Laura Palmer?") | |
st.write("### The first Twin Peaks Question Answering system!") | |
st.markdown("""<br/> | |
Ask any question on Twin Peaks and see if the systsem can find the correct answer to your query! | |
*Note: do not use keywords, but full-fledged questions.* | |
""", unsafe_allow_html=True) | |
# Sidebar | |
st.sidebar.header("Who killed Laura Palmer?") | |
st.sidebar.image("https://upload.wikimedia.org/wikipedia/it/3/39/Twin-peaks-1990.jpg") | |
st.sidebar.markdown("#### Twin Peaks Question Answering system") | |
st.sidebar.markdown(f""" | |
<style> | |
a {{ | |
text-decoration: none; | |
}} | |
.haystack-footer {{ | |
text-align: center; | |
}} | |
.haystack-footer h4 {{ | |
margin: 0.1rem; | |
padding:0; | |
}} | |
footer {{ | |
opacity: 0; | |
}} | |
.haystack-footer img {{ | |
display: block; | |
margin-left: auto; | |
margin-right: auto; | |
width: 85%; | |
}} | |
</style> | |
<div class="haystack-footer"> | |
<p>Get it on <a href="https://github.com/deepset-ai/haystack/">GitHub</a> - | |
Built with <a href="https://github.com/deepset-ai/haystack/">Haystack</a><br/> | |
<small>Data crawled from <a href="https://twinpeaks.fandom.com/wiki/Twin_Peaks_Wiki">Twin Peaks Wiki</a>.</small> | |
</p> | |
<img src = 'https://static.wikia.nocookie.net/twinpeaks/images/e/ef/Laura_Palmer%2C_the_Queen_Of_Hearts.jpg'/> | |
<br/> | |
</div> | |
""", unsafe_allow_html=True) | |
# st.sidebar.image('https://static.wikia.nocookie.net/twinpeaks/images/e/ef/Laura_Palmer%2C_the_Queen_Of_Hearts.jpg', width=270) #use_column_width='always' | |
song_i = random.randint(1,11) | |
st.sidebar.audio(f'http://twinpeaks.narod.ru/Media/0{song_i}.mp3') | |
# Search bar | |
question = st.text_input("", | |
value=st.session_state.question, | |
max_chars=100, | |
#on_change=reset_results | |
) | |
col1, col2 = st.columns(2) | |
col1.markdown("<style>.stButton button {width:100%;}</style>", unsafe_allow_html=True) | |
col2.markdown("<style>.stButton button {width:100%;}</style>", unsafe_allow_html=True) | |
# Run button | |
run_pressed = col1.button("Run") | |
run_query = (run_pressed or question != st.session_state.question) and not st.session_state.random_question_requested | |
# Get results for query | |
if run_query and question: | |
reset_results() | |
st.session_state.question = question | |
with st.spinner( | |
"π§ Performing neural search on documents..." | |
): | |
try: | |
st.session_state.results, st.session_state.raw_json = query(pipe, question) | |
except JSONDecodeError as je: | |
st.error("π An error occurred reading the results. Is the document store working?") | |
return | |
except Exception as e: | |
logging.exception(e) | |
if "The server is busy processing requests" in str(e) or "503" in str(e): | |
st.error("π§βπΎ All our workers are busy! Try again later.") | |
else: | |
st.error("π An error occurred during the request.") | |
return | |
if st.session_state.results: | |
st.write("## Results:") | |
alert_irrelevance=True | |
for count, result in enumerate(st.session_state.results['answers']): | |
result=result.to_dict() | |
if result["answer"]: | |
if alert_irrelevance and result['score']<=0.40: | |
alert_irrelevance = False | |
st.write("<h3 style='color: red'>Attention, the following answers have low relevance:</h3>", unsafe_allow_html=True) | |
answer, context = result["answer"], result["context"] | |
#authors, title = result["meta"]["authors"], result["meta"]["title"] | |
start_idx = context.find(answer) | |
end_idx = start_idx + len(answer) | |
#url = get_backlink(result, my_ip) | |
# Hack due to this bug: https://github.com/streamlit/streamlit/issues/3190 | |
st.write(markdown("- ..."+context[:start_idx] + str(annotation(answer, "ANSWER", "#8ef")) + context[end_idx:]+"..."), unsafe_allow_html=True) | |
#st.write(markdown(f"<a href='{url}'>{title} - <i>{authors}</i></a>"), unsafe_allow_html=True) | |
#st.write(markdown(f"**Relevance:** {result['score']:.2f}"), unsafe_allow_html=True) | |
main() | |