from transformers import pipeline
import streamlit as st

def bias_evaluation_presentation():
    st.title("A brief note on Bias and evaluation")
    st.subheader("You can check yourself if the model is biased or toxic !")
    st.markdown("""
    ### Evaluate a generated content
    """)

def toxicity_classif(text):
    model_path = "citizenlab/distilbert-base-multilingual-cased-toxicity"
    
    toxicity_classifier = pipeline("text-classification", model=model_path, tokenizer=model_path, from_pt=True)
    result = toxicity_classifier(text)
    st.markdown(f"""
    ### Result
    
    This content is evaluated as {result[0]["label"]} with a score of {result[0]["score"]}
    """)


bias_evaluation_presentation()

txt = st.text_area(
    "Input the generated content here"
)

toxicity_classif(txt)