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import sys | |
import toml | |
from omegaconf import OmegaConf | |
from query import VectaraQuery | |
import os | |
import streamlit as st | |
from PIL import Image | |
def launch_bot(): | |
def generate_response(question): | |
response = vq.submit_query(question) | |
return response | |
if 'cfg' not in st.session_state: | |
corpus_ids = str(os.environ['corpus_ids']).split(',') | |
questions = list(eval(os.environ['examples'])) | |
cfg = OmegaConf.create({ | |
'customer_id': str(os.environ['customer_id']), | |
'corpus_ids': corpus_ids, | |
'api_key': str(os.environ['api_key']), | |
'title': os.environ['title'], | |
'description': os.environ['description'], | |
'examples': questions, | |
'source_data_desc': os.environ['source_data_desc'] | |
}) | |
st.session_state.cfg = cfg | |
st.session_state.vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_ids) | |
cfg = st.session_state.cfg | |
vq = st.session_state.vq | |
st.set_page_config(page_title=cfg.title, layout="wide") | |
# left side content | |
with st.sidebar: | |
image = Image.open('Vectara-logo.png') | |
st.markdown(f"## Welcome to {cfg.title}\n\n" | |
f"With this demo uses Retieval Augmented Generation to ask questions about {cfg.source_data_desc}\n\n") | |
st.markdown("---") | |
st.markdown( | |
"## How this works?\n" | |
"This app was built with [Vectara](https://vectara.com).\n" | |
"Vectara's [Indexing API](https://docs.vectara.com/docs/api-reference/indexing-apis/indexing) was used to ingest the data into a Vectara corpus (or index).\n\n" | |
"This app uses Vectara Chat API to query the corpus and present the results to you, answering your question.\n\n" | |
) | |
st.markdown("---") | |
st.image(image, width=250) | |
st.markdown(f"<center> <h2> Vectara chat demo: {cfg.title} </h2> </center>", unsafe_allow_html=True) | |
st.markdown(f"<center> <h4> {cfg.description} <h4> </center>", unsafe_allow_html=True) | |
if "messages" not in st.session_state.keys(): | |
st.session_state.messages = [{"role": "assistant", "content": "How may I help you?"}] | |
# Display chat messages | |
for message in st.session_state.messages: | |
with st.chat_message(message["role"]): | |
st.write(message["content"]) | |
# User-provided prompt | |
if prompt := st.chat_input(): | |
st.session_state.messages.append({"role": "user", "content": prompt}) | |
with st.chat_message("user"): | |
st.write(prompt) | |
# Generate a new response if last message is not from assistant | |
if st.session_state.messages[-1]["role"] != "assistant": | |
with st.chat_message("assistant"): | |
with st.spinner("Thinking..."): | |
response = generate_response(prompt) | |
st.write(response) | |
message = {"role": "assistant", "content": response} | |
st.session_state.messages.append(message) | |
if __name__ == "__main__": | |
launch_bot() | |