Create pdf_summarizer.py

pdf_summarizer.py

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+# Install the required packages before running this script
+# You can uncomment the following line to install packages directly (if running in a local environment)
+# !pip install transformers torch PyPDF2 gradio
+
+import gradio as gr
+from transformers import pipeline
+import PyPDF2
+
+# Load the summarization pipeline
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def pdf_to_text(pdf_file):
+    """Extract text from a PDF file."""
+    text = ""
+    with open(pdf_file, 'rb') as file:
+        reader = PyPDF2.PdfReader(file)
+        for page in reader.pages:
+            text += page.extract_text() + "\n"
+    return text
+
+def summarize_pdf(pdf_file):
+    """Summarize the content of a PDF file."""
+    text = pdf_to_text(pdf_file)
+    if len(text) == 0:
+        return "No text found in the PDF."
+    
+    # Summarize the text
+    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
+    return summary[0]['summary_text']
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=summarize_pdf,
+    inputs=gr.File(label="Upload a PDF file"),
+    outputs=gr.Textbox(label="Summary"),
+    title="PDF Summarizer",
+    description="Upload a PDF file to receive a summary."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    interface.launch()