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()