Update app.py

app.py

@@ -1,40 +1,21 @@
+!pip install transformers
+!pip install gradio
+
 import gradio as gr
 from transformers import pipeline
-from nltk.tokenize import sent_tokenize
-pip install nltk
 
-# Initialize the summarizer pipelines (abstractive and extractive)
-summarizer_abstractive = pipeline("summarization", model="facebook/bart-large-cnn")
-summarizer_extractive = pipeline("summarization", model="bert-extractive-summarizer")
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
 
-# Function to summarize text using the selected model
-def summarize_text(text, model_type="Abstractive", max_length=150, min_length=50):
-    # Tokenize the text into sentences
-    sentences = sent_tokenize(text)
-    if model_type == "Abstractive":
-        # Process using the abstractive model (BART)
-        summary = summarizer_abstractive(text, max_length=max_length, min_length=min_length, do_sample=False)
-        return summary[0]['summary_text']
-    
-    elif model_type == "Extractive":
-        # Process using the extractive model (BERT)
-        summary = summarizer_extractive(text)
-        return ' '.join([sentence['sentence'] for sentence in summary])
+def summarize_text(text):
+    summary = summarizer(text, max_length=200, min_length=100, do_sample=False)
+    return summary[0]['summary_text']
 
-# Create Gradio Interface
 demo = gr.Interface(
     fn=summarize_text,
-    inputs=[
-        gr.Textbox(placeholder="Enter your long text here", label="Input Text", lines=10),
-        gr.Radio(choices=["Abstractive", "Extractive"], label="Summarization Method", value="Abstractive"),
-        gr.Slider(minimum=50, maximum=500, step=10, label="Max Length", value=150),
-        gr.Slider(minimum=10, maximum=150, step=5, label="Min Length", value=50),
-    ],
-    outputs="text",
-    title="Advanced Text Summarizer",
-    description="This tool provides both abstractive and extractive summarization options, allowing you to select the best method and adjust summary length.",
-    live=True,
+    inputs=gr.Textbox(placeholder="Enter your text here", label="Input Text"),
+    outputs=gr.Textbox(label="Summary"),
+    title="Text Summarizer",
+    description="This chatbot takes a long text as input and returns a summary."
 )
 
-# Launch the interface
 demo.launch()