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import streamlit as st
import torch
import uuid
import nest_asyncio
import asyncio
import os
#import omegaConf
torch.classes.__path__ = []
# Setup for HTTP API Calls
if 'device_id' not in st.session_state:
st.session_state.device_id = str(uuid.uuid4())
if "feedback_key" not in st.session_state:
st.session_state.feedback_key = 0
#corpus_keys = 'first.last'
def launch_bot():
def reset():
st.session_state.messages = [{"role": "assistant", "content": "How may I help you?", "avatar": '🤖'}]
st.session_state.ex_prompt = None
st.session_state.first_turn = True
def generate_response(question):
response = vq.submit_query(question, languages[st.session_state.language])
return response
def generate_streaming_response(question):
response = vq.submit_query_streaming(question, languages[st.session_state.language])
return response
def show_example_questions():
if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:
selected_example = pills("Questions to Try:", st.session_state.example_messages, index=None)
if selected_example:
st.session_state.ex_prompt = selected_example
st.session_state.first_turn = False
return True
return False
if 'cfg' not in st.session_state:
#corpus_keys = str(os.environ["first, last"]).split(',')
cfg = "SBS MMMMAPPPPEEERR", # omegaConf.create({
# 'corpus_keys': corpus_keys,
# 'api_key': str(os.environ['api_key']),
# 'title': os.environ['title'],
# 'source_data_desc': os.environ['source_data_desc'],
# 'streaming': isTrue(os.environ.get('streaming', False)),
# 'prompt_name': os.environ.get('prompt_name', None),
# 'examples': os.environ.get('examples', None),
# 'language': 'English'
#})
#st.session_state.cfg = cfg
#st.session_state.ex_prompt = None
#st.session_state.first_turn = True
#st.session_state.language = cfg.language
#example_messages = [example.strip() for example in cfg.examples.split(",")]
#st.session_state.example_messages = [em for em in example_messages if len(em)>0][:max_examples]
#st.session_state.vq = VectaraQuery(cfg.api_key, cfg.corpus_keys, cfg.prompt_name)
#cfg = st.session_state.cfg
#vq = st.session_state.vq
st.set_page_config(page_title=cfg, layout="wide")
# left side content
with st.sidebar:
#image = Image.open('Vectara-logo.png')
#st.image(image, width=175)
st.markdown(f"## About\n\n"
f"This demo uses outside RAG to ask questions about {cfg.source_data_desc}\n")
#cfg.language = st.selectbox('Language:', languages.keys())
#if st.session_state.language != cfg.language:
# st.session_state.language = cfg.language
# reset()
# st.rerun()
st.markdown("\n")
bc1, _ = st.columns([1, 1])
with bc1:
if st.button('Start Over'):
reset()
st.rerun()
st.markdown("---")
st.markdown(
"## Temporary test demo only\n"
)
st.markdown(f"<center> <h2> Header Demo Test: {cfg} </h2> </center>", unsafe_allow_html=True)
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"])
example_container = st.empty()
with example_container:
if show_example_questions():
example_container.empty()
st.rerun()
# select prompt from example question or user provided input
if st.session_state.ex_prompt:
prompt = st.session_state.ex_prompt
else:
prompt = st.chat_input()
if prompt:
st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑💻'})
with st.chat_message("user", avatar="🧑💻"):
st.write(prompt)
st.session_state.ex_prompt = None
# 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="🤖"):
if cfg.streaming:
stream = generate_streaming_response(prompt)
response = st.write_stream(stream)
else:
with st.spinner("Thinking..."):
response = generate_response(prompt)
st.write(response)
response = escape_dollars_outside_latex(response)
message = {"role": "assistant", "content": response, "avatar": '🤖'}
st.session_state.messages.append(message)
# Send query and response to Amplitude Analytics
send_amplitude_data(
user_query=st.session_state.messages[-2]["content"],
chat_response=st.session_state.messages[-1]["content"],
demo_name=cfg #["title"],
language=st.session_state.language
)
st.rerun()
if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != "How may I help you?"):
streamlit_feedback(feedback_type="thumbs", on_submit = thumbs_feedback, key = st.session_state.feedback_key,
kwargs = {"user_query": st.session_state.messages[-2]["content"],
"chat_response": st.session_state.messages[-1]["content"],
"demo_name": cfg #["title"],
"response_language": st.session_state.language})
if __name__ == "__main__":
st.set_page_config(page_title="Sticky toolbar test", layout="wide")
nest_asyncio.apply()
asyncio.run(launch_bot())
for i in range(100):
st.write(f"This is scrollable content line {i}")
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