Update app.py

app.py

@@ -0,0 +1,43 @@
+import gradio as gr
+from transformers import pipeline
+
+# Initialize summarization pipeline
+summarizer = pipeline("summarization", model="t5-small", revision="main")
+
+# Function to summarize text
+def summarize_text(text, model):
+    summary = model(text)[0]['summary_text']
+    return summary
+
+# Function to read PDF and summarize
+def summarize_pdf(pdf_file, model):
+    import fitz  # PyMuPDF
+    with fitz.open(pdf_file.name) as doc:
+        text = ""
+        for page in doc:
+            text += page.get_text()
+    return summarize_text(text, model)
+
+# Gradio Interface
+def summarize(input_text, uploaded_file):
+    if input_text:
+        summary = summarize_text(input_text, summarizer)
+    else:
+        summary = summarize_pdf(uploaded_file, summarizer)
+    return summary
+
+inputs = [
+    gr.Textbox(lines=10, label="Enter Text to Summarize"),
+    gr.File(label="Upload PDF file")
+]
+output = gr.Textbox(label="Summary")
+
+gr.Interface(
+    fn=summarize,
+    inputs=inputs,
+    outputs=output,
+    title="Text Summarization App",
+    description="Summarize text or PDF files using pre-trained models.",
+    theme="compact",  # Example theme
+    layout="horizontal"  # Example layout
+).launch()