Create app.py

app.py

@@ -0,0 +1,35 @@
+import gradio as gr
+from PyPDF2 import PdfReader
+from transformers import pipeline
+
+# Load the pre-trained model for Q&A
+qa_pipeline = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")
+
+def extract_text_from_pdf(pdf):
+    # Extract text from the uploaded PDF
+    reader = PdfReader(pdf)
+    text = ""
+    for page in reader.pages:
+        text += page.extract_text()
+    return text
+
+def generate_qa(pdf, question):
+    # Extract PDF content
+    content = extract_text_from_pdf(pdf)
+    
+    # Perform question-answering
+    answer = qa_pipeline(question=question, context=content)
+    return answer["answer"]
+
+# Create the Gradio app interface
+with gr.Blocks() as app:
+    gr.Markdown("## PDF Q&A Application")
+    
+    pdf_file = gr.File(label="Upload PDF", type="file")
+    question = gr.Textbox(label="Ask a question about the PDF")
+    answer = gr.Textbox(label="Answer")
+    
+    btn = gr.Button("Submit")
+    btn.click(generate_qa, inputs=[pdf_file, question], outputs=answer)
+
+app.launch()