Update app.py

app.py

@@ -1,20 +1,14 @@
 import streamlit as st
 from transformers import pipeline
-from PIL import Image
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+pipeline = pipeline(task="conversational", model="lmsys/fastchat-t5-3b-v1.0")
 
-st.title("Hot Dog? Or Not?")
+st.title("Conversational AI with FastChat")
 
-file_name = st.file_uploader("Upload a hot dog candidate image")
+query = st.text_input("Enter your query:")
 
-if file_name is not None:
-    col1, col2 = st.columns(2)
+if query is not None:
+    response = pipeline(query)
 
-    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)}%")
+    st.subheader("Response:")
+    st.write(response["text"])