Create app.py

app.py

@@ -0,0 +1,44 @@
+import gradio as gr
+from transformers import pipeline
+import torch
+
+
+# Load the BART model for summarization
+summarizer = pipeline("summarization", 
+                      model="facebook/bart-large-cnn")
+
+# Function to summarize the input text
+def summarize_text(input_text):
+
+
+    # Ensure the text is not too short for summarization
+    if len(input_text.split()) < 10:
+        return "Please provide a longer text for summarization."
+
+    # Summarize the text using BART
+    summarized_output = summarizer(input_text, 
+                                   min_length=10, 
+                                   max_length=100, 
+                                   do_sample=False)
+    return summarized_output[0]['summary_text']
+
+# Create the Gradio interface
+interface = gr.Interface(
+    fn=summarize_text,  # Function that summarizes the input
+    
+    inputs=gr.Textbox(label="Input Text", 
+                      lines=10, 
+                      placeholder="Enter a long piece of text here..."),  # Text input field
+
+    
+    outputs=gr.Textbox(label="Summarized Text"),  # Output field for the summarized text
+    
+    title="Text Summarizer",  # Title of the app
+    
+    description="Enter a text, and this app will summarize it using the BART model. The summary will be between 10 and 100 tokens.",  # Description
+    
+    live=False,  # Disable live updates while typing
+)
+
+# Launch the interface
+interface.launch()