Update app.py

app.py

@@ -1,29 +1,49 @@
 import streamlit as st
-from transformers import pipeline
+import json
+import requests
+
+
+
+headers = {"Authorization": f"Bearer {API_TOKEN}"}
+API_URL = "https://api-inference.huggingface.co/models/sabre-code/pegasus-large-cnn-dailymail"
+
+
+def query(payload):
+    data = json.dumps(payload)
+    response = requests.request("POST", API_URL, headers=headers, data=data)
+    return json.loads(response.content.decode("utf-8"))
+
+
 
 st.set_page_config(layout='wide')
-st.title("Text Summarization App PEGASUS-Large) ")
+st.title("Text Summarisation App PEGASUS-large")
 st.subheader('Input text below to be summarised', divider='rainbow')
+
+
 # Create a text input widget
 text_input = st.text_area(label="Input Text", height=200)
 generated_summary = ""
 # Define a function to generate the summary
 def generate_summary(text):
-    summarizer = pipeline("summarization", model="sabre-code/pegasus-large-cnn-dailymail")
-    generated_summary = summarizer(text)
+    def query(payload):
+        data = json.dumps(payload)
+        response = requests.request("POST", API_URL, headers=headers, data=data)
+        return json.loads(response.content.decode("utf-8"))
+    
+    data = query({"inputs": text})
     
     
     # Return the generated summary
-    return generated_summary['summary_text']
+    return data
 
 # Add a button to trigger the generation of the summary
 generate_button = st.button(label="Generate Summary")
 if generate_button:
     # Call the generate_summary function when the button is clicked
     generated_summary = generate_summary(text_input)
-    st.success("Summary Generated!")
+    #st.success("Summary Generated!")
 
 
 # Display the generated summary
 st.markdown("## Summary")
-st.code(generated_summary)
+st.success(generated_summary)