Stefano Fiorucci
Update app.py
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# inspired by https://github.com/deepset-ai/haystack/blob/master/ui/webapp.py
import time
import streamlit as st
import logging
from json import JSONDecodeError
from markdown import markdown
from annotated_text import annotation
from urllib.parse import unquote
import random
from app_utils.backend_utils import load_questions, query
from app_utils.frontend_utils import (set_state_if_absent, reset_results,
SIDEBAR_STYLE, TWIN_PEAKS_IMG_SRC, LAURA_PALMER_IMG_SRC, SPOTIFY_IFRAME)
from app_utils.config import RETRIEVER_TOP_K, READER_TOP_K, LOW_RELEVANCE_THRESHOLD
def main():
questions = load_questions()
# 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)
## SIDEBAR
st.markdown(SIDEBAR_STYLE, unsafe_allow_html=True)
st.sidebar.header("Who killed Laura Palmer?")
st.sidebar.image(TWIN_PEAKS_IMG_SRC)
st.sidebar.markdown(f"""
<p align="center"><b>Twin Peaks Question Answering system</b></p>
<div class="haystack-footer">
<p><a href="https://github.com/anakin87/who-killed-laura-palmer" target="_blank">GitHub</a> -
Built with <a href="https://github.com/deepset-ai/haystack/" target="_blank">Haystack</a><br/>
<small>Data crawled from <a href="https://twinpeaks.fandom.com/wiki/Twin_Peaks_Wiki" target="_blank">
Twin Peaks Wiki</a>.</small>
<img src="https://visitor-badge.glitch.me/badge?page_id=wklp">
</p><img src="{LAURA_PALMER_IMG_SRC}"/><br/></div>
""", unsafe_allow_html=True)
# spotify webplayer
st.sidebar.markdown(SPOTIFY_IFRAME, unsafe_allow_html=True)
## MAIN CONTAINER
st.write("# Who killed Laura Palmer?")
st.write("### The first Twin Peaks Question Answering system!")
st.markdown("""
Ask any question about [Twin Peaks]
(https://twinpeaks.fandom.com/wiki/Twin_Peaks)
and see if the AI ​​can find an answer...
*Note: do not use keywords, but full-fledged questions.*
""")
# 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")
# Random question button
if col2.button("Random question"):
reset_results()
question = random.choice(questions)
# Avoid picking the same question twice (the change is not visible on the UI)
while question == st.session_state.question:
question = random.choice(questions)
st.session_state.question = question
st.session_state.random_question_requested = True
# Re-runs the script setting the random question as the textbox value
# Unfortunately necessary as the Random Question button is _below_ the textbox
raise st.script_runner.RerunException(
st.script_request_queue.RerunData(None))
else:
st.session_state.random_question_requested = False
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:
time_start = time.time()
reset_results()
st.session_state.question = question
with st.spinner("🧠 &nbsp;&nbsp; Performing neural search on documents..."):
try:
st.session_state.results = query(
question, RETRIEVER_TOP_K, READER_TOP_K)
time_end = time.time()
print(f'elapsed time: {time_end - time_start}')
except JSONDecodeError as je:
st.error(
"πŸ‘“ &nbsp;&nbsp; An error occurred reading the results. Is the document store working?")
return
except Exception as e:
logging.exception(e)
st.error("🐞 &nbsp;&nbsp; An error occurred during the request.")
return
# Display results
if st.session_state.results:
st.write("## Results:")
alert_irrelevance = True
if len(st.session_state.results['answers']) == 0:
st.info("""πŸ€” &nbsp;&nbsp; Haystack is unsure whether any of
the documents contain an answer to your question. Try to reformulate it!""")
for result in st.session_state.results['answers']:
result = result.to_dict()
if result["answer"]:
if alert_irrelevance and result['score'] < LOW_RELEVANCE_THRESHOLD:
alert_irrelevance = False
st.write("""
<h4 style='color: darkred'>Attention, the
following answers have low relevance:</h4>""",
unsafe_allow_html=True)
answer, context = result["answer"], result["context"]
start_idx = context.find(answer)
end_idx = start_idx + len(answer)
# Hack due to this bug: https://github.com/streamlit/streamlit/issues/3190
st.write(markdown("- ..."+context[:start_idx] +
str(annotation(answer, "ANSWER", "#3e1c21", "white")) +
context[end_idx:]+"..."), unsafe_allow_html=True)
source = ""
name = unquote(result['meta']['name']).replace('_', ' ')
url = result['meta']['url']
source = f"[{name}]({url})"
st.markdown(
f"**Score:** {result['score']:.2f} - **Source:** {source}")
main()