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| import streamlit as st | |
| import time | |
| import logging | |
| from json import JSONDecodeError | |
| # from markdown import markdown | |
| # from annotated_text import annotation | |
| # from urllib.parse import unquote | |
| import random | |
| import pandas as pd | |
| from app_utils.backend_utils import load_statements, query | |
| from app_utils.frontend_utils import set_state_if_absent, reset_results, entailment_html_messages | |
| from app_utils.config import RETRIEVER_TOP_K | |
| def main(): | |
| statements = load_statements() | |
| # 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) | |
| ## MAIN CONTAINER | |
| 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 | |
| # raise st.script_runner.RerunException( | |
| # st.script_request_queue.RerunData(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("🧠 Performing neural search on documents..."): | |
| try: | |
| st.session_state.results = query( | |
| statement, RETRIEVER_TOP_K) | |
| 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( | |
| "👓 An error occurred reading the results. Is the document store working?") | |
| return | |
| except Exception as e: | |
| logging.exception(e) | |
| st.error("🐞 An error occurred during the request.") | |
| return | |
| # Display results | |
| if st.session_state.results: | |
| results = st.session_state.results | |
| docs, agg_entailment_info = results['documents'], results['agg_entailment_info'] | |
| print(results) | |
| max_key = max(agg_entailment_info, key=agg_entailment_info.get) | |
| message = entailment_html_messages[max_key] | |
| st.markdown(f'<h4>{message}</h4>', unsafe_allow_html=True) | |
| st.markdown(f'###### Aggregate entailment information:') | |
| st.write(results['agg_entailment_info']) | |
| st.markdown(f'###### Relevant snippets:') | |
| # colms = st.columns((2, 5, 1, 1, 1, 1)) | |
| # fields = ["Page title",'Content', 'Relevance', 'contradiction', 'neutral', 'entailment'] | |
| # for col, field_name in zip(colms, fields): | |
| # # header | |
| # col.write(field_name) | |
| df = [] | |
| for doc in docs: | |
| # col1, col2, col3, col4, col5, col6 = st.columns((2, 5, 1, 1, 1, 1)) | |
| # col1.write(f"[{doc.meta['name']}]({doc.meta['url']})") | |
| # col2.write(f"{doc.content}") | |
| # col3.write(f"{doc.score:.3f}") | |
| # col4.write(f"{doc.meta['entailment_info']['contradiction']:.2f}") | |
| # col5.write(f"{doc.meta['entailment_info']['neutral']:.2f}") | |
| # col6.write(f"{doc.meta['entailment_info']['entailment']:.2f}") | |
| # 'con': f"{doc.meta['entailment_info']['contradiction']:.2f}", | |
| # 'neu': f"{doc.meta['entailment_info']['neutral']:.2f}", | |
| # 'ent': f"{doc.meta['entailment_info']['entailment']:.2f}", | |
| # # 'url': doc.meta['url'], | |
| # 'Content': doc.content} | |
| # | |
| # | |
| # | |
| row = {'Title': doc.meta['name'], | |
| 'Relevance': f"{doc.score:.3f}", | |
| 'con': f"{doc.meta['entailment_info']['contradiction']:.2f}", | |
| 'neu': f"{doc.meta['entailment_info']['neutral']:.2f}", | |
| 'ent': f"{doc.meta['entailment_info']['entailment']:.2f}", | |
| # 'url': doc.meta['url'], | |
| 'Content': doc.content} | |
| df.append(row) | |
| st.dataframe(pd.DataFrame(df))#.style.apply(highlight)) | |
| # if len(st.session_state.results['answers']) == 0: | |
| # st.info("""🤔 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}") | |
| # def make_pretty(styler): | |
| # styler.set_caption("Weather Conditions") | |
| # # styler.format(rain_condition) | |
| # styler.format_con(lambda v: v.float(v)) | |
| # styler.background_gradient(axis=None, vmin=0, vmax=1, cmap="YlGnBu") | |
| # return styler | |
| def highlight(s): | |
| return ['background-color: red']*5 | |
| main() |