app.py checking in

app.py

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+import torch
+import gradio as gr
+import fitz # PyMuPDF
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+qna = pipeline("question-answering", model="deepset/roberta-base-squad2")
+
+
+def read_pdf(file_path):
+    try:
+        # Open the PDF file
+        pdf_document = fitz.open(file_path)
+
+        # Initialize a string to store the content
+        content = ""
+
+        # Iterate through each page
+        for page_num in range(len(pdf_document)):
+            page = pdf_document.load_page(page_num)  # Load the page
+            content += page.get_text()  # Extract text from the page
+
+        # Close the PDF file
+        pdf_document.close()
+
+        return content
+    except Exception as e:
+        return str(e)
+
+def answer_question(file_path, question):
+    context = read_pdf(file_path)
+    answer = qna(question= question, context=context)
+    return answer['answer']
+
+gr.close_all()
+
+
+demo = gr.Interface(answer_question,
+                    inputs=[gr.File(file_types=['pdf'], label='Upload a pdf file'), gr.Textbox(label='Please ask question?', lines=3)],
+
+                    outputs=[gr.Textbox(label='Answer is:', lines=3)],
+                    title="Gen AI Learning Project 5: Question and Answer with PDF file",
+                    description="This Application uses 'deepset/roberta-base-squad2' to simple short answer from PDF content to questions asked.")
+demo.launch()
+