Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import pytesseract
+from PIL import Image
+
+# Load the NLP model for text simplification
+simplify_model = pipeline("summarization", model="t5-small")
+
+def process_image(image):
+    """
+    Extract text from an uploaded image and simplify it.
+    """
+    # Extract text using Tesseract OCR
+    text = pytesseract.image_to_string(Image.open(image))
+    
+    # Check if text is empty
+    if not text.strip():
+        return "No text detected in the image. Please upload a clear image of the text."
+
+    # Simplify the extracted text
+    simplified_text = simplify_model(text, max_length=50, min_length=10, do_sample=False)[0]['summary_text']
+    return simplified_text
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=process_image,
+    inputs="image",
+    outputs="text",
+    title="Simplify Book Content",
+    description="Upload a photo of a book page to get a simplified explanation in simple English."
+)
+
+# Launch the app
+if __name__ == "__main__":
+    interface.launch()