Update app.py

app.py

@@ -1,9 +1,29 @@
+# import os
+# import matplotlib
+# matplotlib.use('Agg')  # Use the 'Agg' backend for non-interactive use
+# import streamlit as st
+# import tkinter as tk
+# from tkinter import scrolledtext
+# import requests
+
+# SECRET_TOKEN = os.getenv("SECRET_TOKEN")
+
+# API_URL = "https://api-inference.huggingface.co/models/ahmedrachid/FinancialBERT-Sentiment-Analysis"
+# headers = {"Authorization": f"Bearer {SECRET_TOKEN}"}
+
+# def query(payload):
+#     response = requests.post(API_URL, headers=headers, json=payload)
+#     return response.json()
+
+# user_query = st.text_area("Enter your text:")
+# if st.button("Analyze Sentiment"):
+#     output = query({"inputs": user_query})
+#     st.text("Sentiment Analysis Output:")
+#     st.text(output[0][0]['label'])
+
+
 import os
-import matplotlib
-matplotlib.use('Agg')  # Use the 'Agg' backend for non-interactive use
 import streamlit as st
-import tkinter as tk
-from tkinter import scrolledtext
 import requests
 
 SECRET_TOKEN = os.getenv("SECRET_TOKEN")
@@ -17,7 +37,12 @@ def query(payload):
 
 user_query = st.text_area("Enter your text:")
 if st.button("Analyze Sentiment"):
-    output = query({"inputs": user_query})
+    # Show loading message while the model is loading
+    with st.spinner("Analyzing..."):
+        # Load the model
+        output = query({"inputs": user_query})
+    
+    # Display results after loading
     st.text("Sentiment Analysis Output:")
     st.text(output[0][0]['label'])