# app.py

import gradio as gr
from PIL import Image
import pytesseract
import sympy

def solve_math_problem(image):
    try:
        # Convert image to grayscale for better OCR performance
        image = image.convert("L")
        
        # Preprocess the image (optional enhancements can be added here)
        # For example, image = image.point(lambda x: 0 if x < 140 else 255, '1')
        
        # Use pytesseract to extract text from the image
        problem_text = pytesseract.image_to_string(image, config='--psm 7')
        
        # Clean and prepare the extracted text
        problem_text = problem_text.strip().replace('\n', '').replace(' ', '')
        
        # Use sympy to parse and solve the equation
        # Handle simple arithmetic and algebraic equations
        expr = sympy.sympify(problem_text)
        solution = sympy.solve(expr)
        
        # Format the solution for display
        if isinstance(solution, list):
            solution = ', '.join([str(s) for s in solution])
        else:
            solution = str(solution)
        
        return f"**Problem:** {problem_text}\n\n**Solution:** {solution}"
        
    except Exception as e:
        return f"**Error processing image:** {str(e)}"

# Create the Gradio interface
demo = gr.Interface(
    fn=solve_math_problem,
    inputs=gr.Image(
        type="pil", 
        label="Upload Handwritten Math Problem",
        image_mode="L"  # Grayscale mode improves OCR accuracy
    ),
    outputs=gr.Markdown(),
    title="Handwritten Math Problem Solver",
    description="Upload an image of a handwritten math problem, and the app will attempt to solve it.",
    examples=[
        ["example_addition.png"],
        ["example_algebra.jpg"]
    ],
    allow_flagging="never",
    webpage_title="Handwritten Math Solver",
    theme="soft"
)

if __name__ == "__main__":
    demo.launch()