import time import streamlit as st import logging import pandas as pd from json import JSONDecodeError from markdown import markdown import random from typing import List, Dict, Any, Tuple, Optional from haystack.document_stores import FAISSDocumentStore from haystack.nodes import EmbeddingRetriever from haystack.pipelines import ExtractiveQAPipeline from haystack.nodes import FARMReader 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 @st.cache(hash_funcs={"builtins.SwigPyObject": lambda _: None}, allow_output_mutation=True) 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 @st.cache() def load_questions(): with open('./data/questions.txt') as fin: questions = [line.strip() for line in fin.readlines()] return questions def set_state_if_absent(key, value): if key not in st.session_state: st.session_state[key] = value 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() 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) # 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 # sidebar style st.markdown( """ """, unsafe_allow_html=True) # spotify webplayer st.sidebar.markdown("""

""", unsafe_allow_html=True) # 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("", unsafe_allow_html=True) col2.markdown("", unsafe_allow_html=True) # Run button run_pressed = col1.button("Run") # Get next random question from the CSV if col2.button("Random question"): reset_results() question = random.choice(questions) while question == st.session_state.question: # Avoid picking the same question twice (the change is not visible on the UI) question = random.choice(questions) st.session_state.question = question # st.session_state.answer = new_row["Answer"].values[0] 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, st.session_state.raw_json = query(pipe, question) time_end=time.time() print(f'elapsed time: {time_end - time_start}') except JSONDecodeError as je: st.error("πŸ‘“    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("πŸ§‘β€πŸŒΎ    All our workers are busy! Try again later.") else: st.error("🐞    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("

Attention, the following answers have low relevance:

", 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", "#3e1c21")) + context[end_idx:]+"..."), unsafe_allow_html=True) source = "" name = result['meta']['name'] url = result['meta']['url'] source = f"[{name}]({url})" st.markdown(f"**Score:** {result['score']:.2f} - **Source:** {source}") else: st.info("πŸ€”    Haystack is unsure whether any of the documents contain an answer to your question. Try to reformulate it!") main()