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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() |