Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load the summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def summarize_text(text, min_length, max_length):
+    if not text.strip():
+        return "Please enter some text to summarize."
+    
+    summary = summarizer(text, min_length=min_length, max_length=max_length, do_sample=False)
+    return summary[0]['summary_text']
+
+# Define the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Text Summarization using BART Model")
+    gr.Markdown("Enter a long piece of text below and adjust the sliders to set summary length, then click 'Summarize' to generate a concise summary.")
+    
+    text_input = gr.Textbox(label="Input Text", placeholder="Enter your text here...", lines=10)
+    min_length_slider = gr.Slider(10, 50, value=10, label="Minimum Summary Length")
+    max_length_slider = gr.Slider(50, 150, value=100, label="Maximum Summary Length")
+    summarize_button = gr.Button("Summarize")
+    output_text = gr.Textbox(label="Summarized Text", lines=5, interactive=False)
+    
+    summarize_button.click(summarize_text, inputs=[text_input, min_length_slider, max_length_slider], outputs=output_text)
+    
+# Launch the Gradio app
+demo.launch()