Update app.py

app.py

@@ -1,34 +1,26 @@
 import streamlit as st
-import pandas as pd
 import zipfile
 import os
-from sentence_transformers import SentenceTransformer, util
-from transformers import pipeline
 
-st.set_page_config(page_title="Multilingual NLI RAG App")
-
-st.title("🌍 Multilingual RAG-style NLI App")
-st.markdown("Upload the `xnli-multilingual-nli-dataset.zip` file from Kaggle to explore relationships between premises and hypotheses in different languages.")
-
-EXTRACT_FOLDER = "extracted_data"
-
-# File upload
-uploaded_file = st.file_uploader("Upload the XNLI dataset ZIP file", type="zip")
-
-if uploaded_file:
-    # Make sure the folder exists
-    if not os.path.exists(EXTRACT_FOLDER):
-        os.makedirs(EXTRACT_FOLDER)
-
-    # Save and extract zip
-    zip_path = os.path.join(EXTRACT_FOLDER, "dataset.zip")
-    with open(zip_path, "wb") as f:
-        f.write(uploaded_file.read())
-
-    with zipfile.ZipFile(zip_path, "r") as zip_ref:
-        zip_ref.extractall(EXTRACT_FOLDER)
-
-    # List available CSVs
-    csv_files = [f for f in os.listdir(EXTRACT_FOLDER) if f.endswith(".csv")]
-    if csv_files:
-        selected_csv = st.selectbox("Choose a language CSV file_
+# Path to your uploaded zip file
+ZIP_FILE = "xnli-multilingual-nli-dataset.zip"
+EXTRACT_DIR = "extracted_data"
+
+# Extract contents and list files
+@st.cache_data
+def extract_and_list():
+    with zipfile.ZipFile(ZIP_FILE, "r") as zip_ref:
+        zip_ref.extractall(EXTRACT_DIR)
+    return os.listdir(EXTRACT_DIR)
+
+# App starts here
+st.set_page_config(page_title="XNLI Multilingual Viewer")
+st.title("📂 XNLI Multilingual Dataset Viewer")
+
+if not os.path.exists(ZIP_FILE):
+    st.error("Zip file not found. Please upload it.")
+else:
+    files = extract_and_list()
+    st.success("Zip file extracted successfully!")
+    st.write("Here are the files inside your dataset:")
+    st.code("\n".join(files), language="text")