Update app.py

app.py

@@ -1,20 +1,25 @@
 import streamlit as st
-from transformers import pipeline
-from PIL import Image
+import requests
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+# Streamlit app title and description
+st.title("AI Quote Explanation")
+st.write("Enter a quote and get an explanation using AI.")
 
-st.title("Hot Dog? Or Not?")
+# User input for the quote
+quote = st.text_input("Enter a quote")
 
-file_name = st.file_uploader("Upload a hot dog candidate image")
+# Check if the user has entered a quote
+if quote:
+    # API endpoint for AI explanation
+    api_endpoint = "https://api.example.com/explain"
 
-if file_name is not None:
-    col1, col2 = st.columns(2)
+    # Send a POST request to the API
+    response = requests.post(api_endpoint, json={"quote": quote})
 
-    image = Image.open(file_name)
-    col1.image(image, use_column_width=True)
-    predictions = pipeline(image)
-
-    col2.header("Probabilities")
-    for p in predictions:
-        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
+    # Check if the request was successful
+    if response.status_code == 200:
+        explanation = response.json()["explanation"]
+        st.write("Explanation:")
+        st.write(explanation)
+    else:
+        st.write("Error occurred. Please try again later.")