Update app.py

app.py

@@ -1,29 +1,42 @@
-# Import necessary libraries
 from transformers import pipeline
 import gradio as gr
 
-# Load the summarization pipeline with the BART-large-cnn model.
-# BART-large-cnn is fine-tuned for news summarization and is available on Hugging Face:contentReference[oaicite:8]{index=8}.
-summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+# Load the BART summarisation pipeline
+summariser = pipeline("summarization", model="facebook/bart-large-cnn")
 
-# Define a function to perform summarization on the input text.
-def summarize_text(text):
-    # Use the summarizer pipeline to generate a summary.
-    # We set min_length and max_length to control the size of the summary:contentReference[oaicite:9]{index=9}.
-    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)[0]['summary_text']
+def summarise(text):
+    summary = summariser(text, max_length=150, min_length=40, do_sample=False)[0]["summary_text"]
     return summary
 
-# Create Gradio interface components for input and output.
-input_text = gr.Textbox(lines=10, label="Input Text", placeholder="Enter or paste text to summarize...")
-output_summary = gr.Textbox(label="Summary")
+# Two example passages for quick testing
+example_texts = [
+    ["Artificial intelligence has progressed rapidly over the past decade. "
+     "New methods in deep learning have made it possible to process vast amounts of data, "
+     "leading to significant advances in language modelling, computer vision, and reinforcement learning. "
+     "As organisations adopt these technologies, questions emerge regarding transparency, fairness, "
+     "and the wider societal impact of automated decision-making."],
 
-demo = gr.Interface(
-    fn=summarize_text,
-    inputs=input_text,
-    outputs=output_summary,
-    title="📝 Text Summarization with BART",
-    description="**Description:** This app summarizes long text into a concise version. "
-                "It uses a pre-trained BART-large-cnn model to generate an abstractive summary of the input text."
-)
+    ["The Industrial Revolution transformed Europe’s economic landscape. "
+     "Mechanised production replaced traditional craft methods, enabling factories to produce goods at a scale "
+     "previously unimaginable. These developments shifted labour patterns, encouraged urban migration, "
+     "and laid the foundations for modern industrial capitalism."]
+]
+
+with gr.Blocks(title="BART Text Summariser") as demo:
+
+    gr.Markdown(
+        """### BART Text Summariser  
+Paste a passage of text and receive a concise summary.  
+Two sample texts are provided below for immediate experimentation."""
+    )
+
+    input_box = gr.Textbox(
+        lines=12,
+        label="Input Text",
+        placeholder="Paste the text you wish to summarise…"
+    )
+
+    output_box = gr.Textbox(
+        lines=10,      # Increased height for the summary output
+        label="Summary"
 
-demo.launch()