import streamlit as st from utils.backend import (get_plain_pipeline, get_retrieval_augmented_pipeline, get_web_retrieval_augmented_pipeline) from utils.ui import left_sidebar, right_sidebar, main_column from utils.constants import BUTTON_LOCAL_RET_AUG st.set_page_config( page_title="Retrieval Augmentation with Haystack", layout="wide" ) left_sidebar() st.markdown("

Reduce Hallucinations 😵‍💫 with Retrieval Augmentation

", unsafe_allow_html=True) st.markdown("
Ask a question about the collapse of the Silicon Valley Bank (SVB).
", unsafe_allow_html=True) col_1, col_2 = st.columns([4, 2], gap="small") with col_1: run_pressed, placeholder_plain_gpt, placeholder_retrieval_augmented = main_column() with col_2: right_sidebar() if st.session_state.get('query') and run_pressed: ip = st.session_state['query'] with st.spinner('Loading pipelines... \n This may take a few mins and might also fail if OpenAI API server is down.'): p1 = get_plain_pipeline() with st.spinner('Fetching answers from plain GPT... ' '\n This may take a few mins and might also fail if OpenAI API server is down.'): answers = p1.run(ip) placeholder_plain_gpt.markdown(answers['results'][0]) if st.session_state.get("query_type", BUTTON_LOCAL_RET_AUG) == BUTTON_LOCAL_RET_AUG: with st.spinner( 'Loading Retrieval Augmented pipeline that can fetch relevant documents from local data store... ' '\n This may take a few mins and might also fail if OpenAI API server is down.'): p2 = get_retrieval_augmented_pipeline() with st.spinner('Getting relevant documents from documented stores and calculating answers... ' '\n This may take a few mins and might also fail if OpenAI API server is down.'): answers_2 = p2.run(ip) else: with st.spinner( 'Loading Retrieval Augmented pipeline that can fetch relevant documents from the web... \ n This may take a few mins and might also fail if OpenAI API server is down.'): p3 = get_web_retrieval_augmented_pipeline() with st.spinner('Getting relevant documents from the Web and calculating answers... ' '\n This may take a few mins and might also fail if OpenAI API server is down.'): answers_2 = p3.run(ip) placeholder_retrieval_augmented.markdown(answers_2['results'][0]) print(answers_2['invocation_context']['documents']) with st.expander("See source:"): src = answers_2['invocation_context']['documents'][0].replace("$", "\$") split_marker = "\n\n" if "\n\n" in src else "\n" src = " ".join(src.split(split_marker))[0:2000] + "..." st.write(src)