app.py

import streamlit as st
from transformers import pipeline

pipe = pipeline("text-generation", model="austenem/Llama-2-7b-arg-quality")
text = st.text_area('Enter argument and topic:')

if text:
    out = pipe(text)
    st.json(out)

# import streamlit as st
# from transformers import pipeline

# arg_pipeline = pipeline("text-generation", model="austenem/Llama-2-7b-arg-quality")

# st.title("Arg Quality Ranker")
# st.write("Enter an argument and topic to analyze argument quality:")

# st.write("Argument:")
# user_argument = st.text_input("", key="argument")
# st.write("Topic:")
# user_topic = st.text_input("", key="topic")

# st.write("Score:")
# if user_argument and user_topic:
#     user_input = f"Below is an argument and the topic it relates to. Please rate the quality of the argument on a scale of 0 to 1, where 0 is very poor and 1 is very good. \n ### Argument: {user_argument} \n ### Topic: {user_topic} \n ### Score: "
#     result = arg_pipeline(user_input)
#     st.write(result[0]["text"])