app.py

from transformers import pipeline
import gradio as gr

# Load the BART summarisation pipeline
summariser = pipeline("summarization", model="facebook/bart-large-cnn")

def summarise(text):
    summary = summariser(text, max_length=150, min_length=40, do_sample=False)[0]["summary_text"]
    return 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."],

    ["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"