import pipeline separately

app.py

@@ -1,7 +1,8 @@
 import streamlit as st
 import transformers
+import pipeline
 
-arg_pipeline = transformers.pipeline("text-generation", model="austenem/Llama-2-7b-arg-quality")
+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:")
@@ -11,7 +12,8 @@ user_argument = st.text_input("", key="argument")
 st.write("Topic:")
 user_topic = st.text_input("", key="topic")
 
-# 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"])
+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"])