import streamlit as st

from tweet_pipeline import TweetPipeline

EMOTION_EMOJIS = {"Anger": "😡", "Joy": "😂", "Optimism": "😉", "Sadness": "😢"}
OFFENSIVE_EMOJIS = {"Offensive": "😈", "Non-Offensive": "😇"}
SENTIMENT_EMOJIS = {"Negative": "❌", "Neutral": "🤷‍♂️", "Positive": "✅"}

tweet_eval = TweetPipeline()

st.title("🐦 Tweet Evaluator")
input_text = st.text_input("")

button = st.button("Evaluate!")

if button and input_text != "":
    with st.spinner("Evaluating tweet..."):
        prediction = tweet_eval(input_text)
    st.success("Tweet successfully evaluated!")
    st.markdown(
        f"{EMOTION_EMOJIS[prediction['emotion']]} **Emotion:** {prediction['emotion']}"
    )
    st.markdown(
        f"{OFFENSIVE_EMOJIS[prediction['offensive']]} **Offensive:** {'Yes' if prediction['offensive'] == 'Offensive' else 'No'}"
    )
    st.markdown(
        f"{SENTIMENT_EMOJIS[prediction['sentiment']]} **Sentiment:** {prediction['sentiment']}"
    )
elif button and not input_text:
    st.warning("Please, introduce a tweet to eval.")