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| import os | |
| import streamlit as st | |
| from langchain.chat_models import ChatOpenAI | |
| from langchain.schema import (AIMessage,HumanMessage,SystemMessage) | |
| from transformers import pipeline | |
| from streamlit_extras.let_it_rain import rain | |
| def get_response(question): | |
| st.session_state.sessionMessages.append(HumanMessage(content=question)) | |
| assistant_answer = chat(st.session_state.sessionMessages ) | |
| st.session_state.sessionMessages.append(AIMessage(content=assistant_answer.content)) | |
| return assistant_answer.content | |
| def get_sentiment(user_input, nlp): | |
| result = nlp(user_input) | |
| sentiment = "" | |
| if (result[0]['label'] == '1 star'): | |
| sentiment = 'very negative' | |
| elif (result[0]['label'] == '2 stars'): | |
| sentiment = 'negative' | |
| elif (result[0]['label'] == '3 stars'): | |
| sentiment = 'neutral' | |
| elif (result[0]['label'] == '4 stars'): | |
| sentiment = 'positive' | |
| else: | |
| sentiment = 'very positive' | |
| prob = result[0]['score'] | |
| return sentiment, prob | |
| # open ai | |
| chat = ChatOpenAI(model="gpt-3.5-turbo", temperature=1) | |
| # hugging-face model | |
| nlp = pipeline(task='sentiment-analysis', model='nlptown/bert-base-multilingual-uncased-sentiment') | |
| st.set_page_config(page_title="HomeX Assistant", page_icon=":robot:") | |
| st.header("Knock knock, It's meeee the JOKER!") | |
| if "sessionMessages" not in st.session_state: | |
| st.session_state.sessionMessages = [SystemMessage(content="You have an evil personality like Joker from Batman")] | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| if user_input := st.chat_input("Say something"): | |
| assistant_input = get_response(user_input) | |
| sentiment, prob = get_sentiment(user_input, nlp) | |
| sentiment_analysis = f" (sentiment:{sentiment},score:{prob})" | |
| # add user input to history | |
| st.session_state.messages.append({"role": "user", "content": user_input}) | |
| # add assistant input to history | |
| st.session_state.messages.append({"role": "assistant", "content": assistant_input}) | |
| # sentiment analysis | |
| if sentiment == "very negative": | |
| rain( | |
| emoji="⛔", | |
| font_size=20, # the size of emoji | |
| falling_speed=3, # speed of raining | |
| animation_length="infinite", # for how much time the animation will happen | |
| ) | |
| elif sentiment == "negative": | |
| rain( | |
| emoji="⛔", | |
| font_size=20, # the size of emoji | |
| falling_speed=3, # speed of raining | |
| animation_length="infinite", # for how much time the animation will happen | |
| ) | |
| elif sentiment == "neutral": | |
| rain( | |
| emoji="😐", | |
| font_size=20, # the size of emoji | |
| falling_speed=3, # speed of raining | |
| animation_length="infinite", # for how much time the animation will happen | |
| ) | |
| elif sentiment == "positive": | |
| rain( | |
| emoji="🟢", | |
| font_size=20, # the size of emoji | |
| falling_speed=3, # speed of raining | |
| animation_length="infinite", # for how much time the animation will happen | |
| ) | |
| elif sentiment == "very positive": | |
| rain( | |
| emoji="🟢", | |
| font_size=20, # the size of emoji | |
| falling_speed=3, # speed of raining | |
| animation_length="infinite", # for how much time the animation will happen | |
| ) | |
| # display chat history | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) |