fact-checking-rocks / Rock_fact_checker.py
anakin87's picture
update streamlit and other libs; better caching; fix graphical appearance
f79211f
raw
history blame
5.21 kB
import random
import time
import logging
from json import JSONDecodeError
import streamlit as st
from app_utils.backend_utils import load_statements, check_statement, explain_using_llm
from app_utils.frontend_utils import (
set_state_if_absent,
reset_results,
entailment_html_messages,
create_df_for_relevant_snippets,
create_ternary_plot,
build_sidebar,
)
from app_utils.config import RETRIEVER_TOP_K
def main():
statements = load_statements()
build_sidebar()
# Persistent state
set_state_if_absent("statement", "Elvis Presley is alive")
set_state_if_absent("answer", "")
set_state_if_absent("results", None)
set_state_if_absent("raw_json", None)
set_state_if_absent("random_statement_requested", False)
st.write("# Fact Checking 🎸 Rocks!")
st.write()
st.markdown(
"""
##### Enter a factual statement about [Rock music](https://en.wikipedia.org/wiki/List_of_mainstream_rock_performers) and let the AI check it out for you...
"""
)
# Search bar
statement = st.text_input(
"", value=st.session_state.statement, 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 statement button
if col2.button("Random statement"):
reset_results()
statement = random.choice(statements)
# Avoid picking the same statement twice (the change is not visible on the UI)
while statement == st.session_state.statement:
statement = random.choice(statements)
st.session_state.statement = statement
st.session_state.random_statement_requested = True
# Re-runs the script setting the random statement as the textbox value
# Unfortunately necessary as the Random statement button is _below_ the textbox
# Adapted for Streamlit>=1.12.0
if hasattr(st, "scriptrunner"):
raise st.scriptrunner.script_runner.RerunException(
st.scriptrunner.script_requests.RerunData(widget_states=None)
)
raise st.runtime.scriptrunner.script_runner.RerunException(
st.runtime.scriptrunner.script_requests.RerunData(widget_states=None)
)
else:
st.session_state.random_statement_requested = False
run_query = (
run_pressed or statement != st.session_state.statement
) and not st.session_state.random_statement_requested
# Get results for query
if run_query and statement:
time_start = time.time()
reset_results()
st.session_state.statement = statement
with st.spinner("🧠 &nbsp;&nbsp; Performing neural search on documents..."):
try:
st.session_state.results = check_statement(statement, RETRIEVER_TOP_K)
print(f"S: {statement}")
time_end = time.time()
print(time.strftime("%Y-%m-%d %H:%M:%S", time.gmtime()))
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:
docs = st.session_state.results["documents"]
agg_entailment_info = st.session_state.results["aggregate_entailment_info"]
# show different messages depending on entailment results
max_key = max(agg_entailment_info, key=agg_entailment_info.get)
message = entailment_html_messages[max_key]
st.markdown(f"<br/><h4>{message}</h4>", unsafe_allow_html=True)
st.markdown(f"###### Aggregate entailment information:")
col1, col2 = st.columns([2, 1])
fig = create_ternary_plot(agg_entailment_info)
with col1:
# theme=None helps to preserve default plotly colors
st.plotly_chart(fig, use_container_width=True, theme=None)
with col2:
st.write(agg_entailment_info)
st.markdown(f"###### Most Relevant snippets:")
df, urls = create_df_for_relevant_snippets(docs)
st.dataframe(df)
str_wiki_pages = "Wikipedia source pages: "
for doc, url in urls.items():
str_wiki_pages += f"[{doc}]({url}) "
st.markdown(str_wiki_pages)
if max_key != "neutral":
st.markdown("#### Why ❓ *(experimental)*")
if st.button("Explain using a Large Language Model πŸ€–..."):
explanation = explain_using_llm(
statement=statement,
documents=docs,
entailment_or_contradiction=max_key,
)
st.markdown(explanation)
main()