Create app.py

app.py

@@ -0,0 +1,37 @@
+import streamlit as st
+from transformers import pipeline
+
+# Initialize the zero-shot classification pipeline
+@st.cache_resource
+def load_classifier():
+    return pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
+
+classifier = load_classifier()
+
+# Streamlit app interface
+st.title("Webpage Subject Classifier")
+st.write(
+    """
+    Enter the text content of a webpage below to classify it into one of the following subjects:
+    - Mathematics
+    - Language Arts
+    - Social Studies
+    - Science
+    """
+)
+
+# Text input area
+text_input = st.text_area("Paste the webpage content here:", height=200)
+
+# Define the candidate labels
+labels = ["Mathematics", "Language Arts", "Social Studies", "Science"]
+
+# Perform classification when the "Classify" button is clicked
+if st.button("Classify"):
+    if text_input.strip():
+        with st.spinner("Classifying..."):
+            result = classifier(text_input, labels)
+            predicted_label = result["labels"][0]
+            st.success(f"The predicted subject is: **{predicted_label}**")
+    else:
+        st.warning("Please enter some text to classify.")