legalaid-chat / app.py
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from omegaconf import OmegaConf
from query import VectaraQuery
import os
import requests
import json
import uuid
import streamlit as st
from streamlit_pills import pills
from streamlit_feedback import streamlit_feedback
from PIL import Image
max_examples = 6
languages = {'English': 'eng', 'Spanish': 'spa', 'French': 'frs', 'Chinese': 'zho', 'German': 'deu', 'Hindi': 'hin', 'Arabic': 'ara',
'Portuguese': 'por', 'Italian': 'ita', 'Japanese': 'jpn', 'Korean': 'kor', 'Russian': 'rus', 'Turkish': 'tur', 'Persian (Farsi)': 'fas',
'Vietnamese': 'vie', 'Thai': 'tha', 'Hebrew': 'heb', 'Dutch': 'nld', 'Indonesian': 'ind', 'Polish': 'pol', 'Ukrainian': 'ukr',
'Romanian': 'ron', 'Swedish': 'swe', 'Czech': 'ces', 'Greek': 'ell', 'Bengali': 'ben', 'Malay (or Malaysian)': 'msa', 'Urdu': 'urd'}
# Setup for HTTP API Calls to Amplitude Analytics
if 'device_id' not in st.session_state:
st.session_state.device_id = str(uuid.uuid4())
headers = {
'Content-Type': 'application/json',
'Accept': '*/*'
}
amp_api_key = os.getenv('AMPLITUDE_TOKEN')
def thumbs_feedback(feedback, **kwargs):
"""
Sends feedback to Amplitude Analytics
"""
data = {
"api_key": amp_api_key,
"events": [{
"device_id": st.session_state.device_id,
"event_type": "provided_feedback",
"event_properties": {
"Space Name": kwargs.get("title", "Unknown Space Name"),
"Demo Type": "chatbot",
"query": kwargs.get("prompt", "No user input"),
"response": kwargs.get("response", "No chat response"),
"feedback": feedback["score"],
"Response Language": st.session_state.language
}
}]
}
response = requests.post('https://api2.amplitude.com/2/httpapi', headers=headers, data=json.dumps(data))
if response.status_code != 200:
print(f"Request failed with status code {response.status_code}. Response Text: {response.text}")
st.session_state.feedback_key += 1
if "feedback_key" not in st.session_state:
st.session_state.feedback_key = 0
def isTrue(x) -> bool:
if isinstance(x, bool):
return x
return x.strip().lower() == 'true'
def launch_bot():
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("Queries 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['corpus_keys']).split(',')
cfg = 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.title, 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 Retrieval Augmented Generation 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
print(f"DEBUG: Language changed to {st.session_state.language}")
st.rerun()
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](https://docs.vectara.com/docs/console-ui/vectara-chat-overview) to query the corpus and present the results to you, answering your question.\n\n"
)
st.markdown("---")
st.markdown(f"<center> <h2> Vectara AI Assistant: {cfg.title} </h2> </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"])
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})
with st.chat_message("user"):
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"):
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)
message = {"role": "assistant", "content": response}
st.session_state.messages.append(message)
# Send query and response to Amplitude Analytics
data = {
"api_key": amp_api_key,
"events": [{
"device_id": st.session_state.device_id,
"event_type": "submitted_query",
"event_properties": {
"Space Name": cfg["title"],
"Demo Type": "chatbot",
"query": st.session_state.messages[-2]["content"],
"response": st.session_state.messages[-1]["content"],
"Response Language": st.session_state.language
}
}]
}
response = requests.post('https://api2.amplitude.com/2/httpapi', headers=headers, data=json.dumps(data))
if response.status_code != 200:
print(f"Amplitude request failed with status code {response.status_code}. Response Text: {response.text}")
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 = {"prompt": st.session_state.messages[-2]["content"],
"response": st.session_state.messages[-1]["content"],
"title": cfg["title"]})
if __name__ == "__main__":
launch_bot()