Create app.py

app.py

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+import streamlit as st
+from docx import Document
+
+import fitz  # PyMuPDF
+from transformers import BartForConditionalGeneration, BartTokenizer, pipeline
+import textwrap
+import tempfile
+
+# Functions for file reading
+def read_txt(file):
+    return file.getvalue().decode("utf-8")
+
+def read_docx(file):
+    doc = Document(file)
+    return " ".join([para.text for para in doc.paragraphs])
+
+def extract_text_from_pdf(file_path):
+    doc = fitz.open(file_path)
+    text = ""
+    for page_num in range(len(doc)):
+        page = doc[page_num]
+        text += page.get_text()
+    doc.close()
+    return text
+
+def read_pdf(file):
+    # Create a temporary file
+    temp_file = tempfile.NamedTemporaryFile(delete=False)        
+    # Write uploaded file content to the temporary file
+    temp_file.write(file.read())
+    # Close the temporary file to ensure changes are saved
+    temp_file.close()
+    # Get the file path of the temporary file
+    file_path = temp_file.name
+
+    return file_path, extract_text_from_pdf(file_path)
+
+# Function for text summarization from pdf
+def text_summarizer_from_pdf(pdf_path):
+    pdf_text = extract_text_from_pdf(pdf_path)
+
+    model_name = "facebook/bart-large-cnn"
+    model = BartForConditionalGeneration.from_pretrained(model_name)
+    tokenizer = BartTokenizer.from_pretrained(model_name)
+
+    inputs = tokenizer.encode("summarize: " + pdf_text, return_tensors="pt", max_length=1024, truncation=True)
+    summary_ids = model.generate(inputs, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)
+
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    formatted_summary = "\n".join(textwrap.wrap(summary, width=80))
+    return formatted_summary
+
+# Summarizer pipeline for txt and docx files
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+st.title("Text Summarizer")
+st.subheader("📁 Upload a pdf, docx or text file to generate a short summary")
+
+# Sidebar to upload file
+uploaded_file = st.sidebar.file_uploader("Choose a file", type=["txt", "pdf", "docx"])
+
+if uploaded_file:
+    file_details = {"FileName:" : uploaded_file.name, "FileType:" : uploaded_file.type, "FileSize:" : uploaded_file.size}
+    for key, value in file_details.items():
+        st.sidebar.write(key, value)
+
+    # Check the file type and read the file
+    if uploaded_file.type == "text/plain":
+        text = read_txt(uploaded_file)
+    elif uploaded_file.type == "application/pdf":
+        temp_path, text = read_pdf(uploaded_file)
+    elif uploaded_file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
+        text = read_docx(uploaded_file)
+    else:
+        st.error("File type not supported. Please upload a txt, pdf or docx file.")
+        st.stop()
+
+    # Generate summary
+    if st.button('Generate Summary'):
+        with st.spinner("Generating summary..."):
+            try:
+                if(uploaded_file.type == "application/pdf"):
+                    pdf_file_path = temp_path
+                    summary = text_summarizer_from_pdf(temp_path)
+                    st.success(summary)
+                else:
+                    summary = summarizer(text, max_length=1000, min_length=30, do_sample=False)
+                    st.success(summary[0]['summary_text'])
+            except Exception as e:
+                st.write(f"Failed to generate summary. Your file may have some problem. Please try again!")