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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> | |
| </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("🧠 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( | |
| "👓 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: | |
| st.write("## Results:") | |
| alert_irrelevance = True | |
| 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}") | |
| main() | |