Create app.py

app.py

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+import os
+import streamlit as st
+from transformers import pipeline
+import torch
+from PyPDF2 import PdfReader
+
+# Disable tokenizers parallelism
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+# Setup for the model
+device = 0 if torch.cuda.is_available() else -1
+summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", device=device)
+
+def split_text(text, max_chunk_size=512):
+    words = text.split()
+    for i in range(0, len(words), max_chunk_size):
+        yield " ".join(words[i:i + max_chunk_size])
+
+def extract_text_from_pdf(pdf_file):
+    reader = PdfReader(pdf_file)
+    text = ""
+    for page_num in range(len(reader.pages)):
+        page = reader.pages[page_num]
+        text += page.extract_text()
+    return text
+
+def summarize_text(text, summarizer):
+    chunks = list(split_text(text))
+    summaries = []
+    for chunk in chunks:
+        input_length = len(chunk.split())
+        max_summary_length = max(10, int(input_length * 0.6))
+        min_summary_length = max(5, int(input_length * 0.2))
+        result = summarizer(chunk, max_length=max_summary_length, min_length=min_summary_length, do_sample=False)
+        summaries.append(result[0]['summary_text'])
+    return " ".join(summaries)
+
+def extract_and_summarize_page_by_page(pdf_file, summarizer):
+    reader = PdfReader(pdf_file)
+    summaries = []
+    for page_num in range(len(reader.pages)):
+        page = reader.pages[page_num]
+        text = page.extract_text()
+        if text:
+            page_summary = summarize_text(text, summarizer)
+            summaries.append(page_summary)
+        else:
+            summaries.append(f"Page {page_num + 1}: No extractable text found.")
+    return summaries
+
+# Streamlit interface
+st.subheader("Generate PDF Summary")
+pdf_file = st.file_uploader("Upload a PDF", type=["pdf"])
+
+if pdf_file:
+    text = extract_text_from_pdf(pdf_file)
+    if len(text) > 0:
+        summaries = extract_and_summarize_page_by_page(pdf_file, summarizer)
+        st.subheader("Summary")
+        for i, summary in enumerate(summaries, 1):
+            st.write(f"### Page {i}\n{summary}\n")
+    else:
+        st.warning("No extractable text found in the PDF.")