Create app.py

app.py

@@ -0,0 +1,46 @@
+from transformers import pipeline
+import fitz  # PyMuPDF
+import gradio as gr
+
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
+def extract_text_from_pdf(pdf_file):
+    try:
+        doc = fitz.open(pdf_file.name)
+        text = ""
+        for page in doc:
+            text += page.get_text()
+        return text
+    except Exception as e:
+        return f"Error extracting text from PDF: {e}"
+
+def summarize_input(text, pdf_file):
+    if pdf_file is not None:
+        text = extract_text_from_pdf(pdf_file)
+        if text.startswith("Error"):
+            return text
+
+    if not text or len(text.strip()) < 30:
+        return "Please provide more text or a valid PDF."
+
+    if len(text) > 3000:
+        text = text[:3000]
+
+    try:
+        summary = summarizer(text, max_length=120, min_length=30, do_sample=False)
+        return summary[0]['summary_text']
+    except Exception as e:
+        return f"Summarization failed: {e}"
+
+app = gr.Interface(
+    fn=summarize_input,
+    inputs=[
+        gr.Textbox(label="Enter Text (leave blank if uploading PDF)", lines=10),
+        gr.File(label="Upload PDF File", file_types=[".pdf"]),
+    ],
+    outputs=gr.Textbox(label="Summary"),
+    title="Text & PDF Summarizer",
+    description="Paste text or upload a PDF to summarize using BART model from Hugging Face."
+)
+
+app.launch()