Create app.py

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+from transformers import pipeline
+from PyPDF2 import PdfReader
+
+# Load summarization model
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+# Function to read and summarize PDF
+def summarize_pdf(pdf_file):
+    if pdf_file is None:
+        return "Please upload a PDF file."
+
+    reader = PdfReader(pdf_file.name)
+    text = ""
+    for page in reader.pages:
+        page_text = page.extract_text()
+        if page_text:
+            text += page_text + "\n"
+
+    # Chunk the text
+    max_chunk = 1000
+    chunks = [text[i:i+max_chunk] for i in range(0, len(text), max_chunk)]
+
+    # Summarize each chunk
+    summaries = []
+    for chunk in chunks:
+        summary = summarizer(chunk, max_length=130, min_length=30, do_sample=False)
+        summaries.append(summary[0]['summary_text'])
+
+    final_summary = " ".join(summaries)
+    return final_summary
+
+
+# Gradio UI
+iface = gr.Interface(
+    fn=summarize_pdf,
+    inputs=gr.File(label="Upload a PDF"),
+    outputs=gr.Textbox(label="Summary"),
+    title="PDF Summarizer",
+    description="Upload a PDF to get a summarized version of its content using Hugging Face transformers."
+)
+
+iface.launch()