language_models_project/app.py

import streamlit as st  # Web App
from main import classify

demo_phrases = """ Here are some examples:
this is a phrase
is it neutral
nothing else to say
man I'm so damn angry
sarcasm lol
I love this product
"""

# title
st.title("Sentiment Analysis")

# subtitle
st.markdown("## A selection of popular sentiment analysis models -  hosted on 🤗 Spaces")

model_name = st.selectbox(
    "Select a pre-trained model",
    [
        "finiteautomata/bertweet-base-sentiment-analysis",
        "ahmedrachid/FinancialBERT-Sentiment-Analysis",
        "finiteautomata/beto-sentiment-analysis",
    ],
)

input_sentences = st.text_area("Sentences", value=demo_phrases, height=200)

data = input_sentences.split("\n")

if st.button("Classify"):
    st.write("Please allow a few minutes for the model to run/download")
    for i in range(len(data)):
        j = classify(model_name.strip(), data[i])[0]
        sentiment = j["label"]
        confidence = j["score"]
        st.write(
            f"{i}. {data[i]} :: Classification - {sentiment} with confidence {confidence}"
        )


st.markdown(
    "Link to the app - [image-to-text-app on 🤗 Spaces](https://huggingface.co/spaces/Amrrs/image-to-text-app)"
)