Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import pdf2image
+import pytesseract
+
+# Initialize model
+qa_model = pipeline("question-answering")
+
+def process_pdf(pdf_file):
+    # Convert PDF to text
+    text = extract_text_from_pdf(pdf_file)
+    return text
+
+def answer_question(question, context):
+    # Get answer from model
+    answer = qa_model(question=question, context=context)
+    return answer['answer']
+
+# Create interface
+with gr.Blocks() as demo:
+    gr.Markdown("# My Study Assistant")
+    
+    # File upload
+    file_input = gr.File(label="Upload PDF")
+    
+    # Text display
+    text_output = gr.Textbox(label="Extracted Text")
+    
+    # Chat interface
+    question = gr.Textbox(label="Ask a question")
+    answer = gr.Textbox(label="Answer")
+    
+    # Buttons
+    upload_btn = gr.Button("Process PDF")
+    ask_btn = gr.Button("Ask")
+    
+    # Set up actions
+    upload_btn.click(process_pdf, inputs=file_input, outputs=text_output)
+    ask_btn.click(answer_question, inputs=[question, text_output], outputs=answer)
+
+demo.launch()