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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("<center> <h2> Reduce Hallucinations 😵💫 with Retrieval Augmentation </h2> </center>", unsafe_allow_html=True)
st.markdown("<center>Ask a question about the collapse of the Silicon Valley Bank (SVB).</center>", 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)
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