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from omegaconf import OmegaConf
from query import VectaraQuery
import streamlit as st
import os
from PIL import Image
def launch_bot():
def generate_response(question):
response = vq.submit_query(question)
return response
def reset():
st.session_state.messages = [{"role": "assistant", "content": "Please ask your question about drink names.", "avatar": '🦖'}]
st.session_state.vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_id, cfg.prompt_name)
if 'cfg' not in st.session_state:
cfg = OmegaConf.create({
'customer_id': str(os.environ['VECTARA_CUSTOMER_ID']),
'corpus_id': '46', # Fixed corpus ID for drink names
'api_key': str(os.environ['VECTARA_API_KEY']),
'prompt_name': 'vectara-experimental-summary-ext-2023-12-11-large',
})
st.session_state.cfg = cfg
st.session_state.vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_id, cfg.prompt_name)
cfg = st.session_state.cfg
vq = st.session_state.vq
st.set_page_config(page_title="Drink Name Query Bot", layout="wide")
# Left side content
with st.sidebar:
image = Image.open('Vectara-logo.png')
st.image(image, width=250)
st.markdown(f"## Welcome to Drink Name Query Bot.\n\n\n")
if st.button('Start Over'):
reset()
st.markdown("---")
st.markdown(
"## How this works?\n"
"This app was built with [Vectara](https://vectara.com).\n\n"
"It demonstrates the use of the Chat functionality along with custom prompts and GPT4-Turbo (as part of our [Scale plan](https://vectara.com/pricing/))"
)
st.markdown("---")
if "messages" not in st.session_state.keys():
reset()
# Display chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"], avatar=message["avatar"]):
st.write(message["content"])
# User-provided prompt
if prompt := st.chat_input():
st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑💻'})
with st.chat_message("user", avatar='🧑💻'):
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", avatar='🤖'):
response = generate_response(prompt)
st.write(response)
message = {"role": "assistant", "content": response, "avatar": '🤖'}
st.session_state.messages.append(message)
if __name__ == "__main__":
launch_bot()
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