Update app.py

app.py

@@ -2,14 +2,17 @@ from transformers import Pix2StructForConditionalGeneration, Pix2StructProcessor
 import gradio as gr
 from PIL import Image
 
+# Use a valid model identifier.
+# Replace "google/matcha-base" with your checkpoint if you have one.
+model_name = "google/matcha-base"
+
 # Load the pre-trained Pix2Struct model and processor
-model_name = "google/pix2struct-mathqa-base"
 model = Pix2StructForConditionalGeneration.from_pretrained(model_name)
 processor = Pix2StructProcessor.from_pretrained(model_name)
 
 # Function to solve handwritten math problems
 def solve_math_problem(image):
-    # Preprocess the image
+    # Preprocess the image: here we render a prompt asking the model to solve the problem.
     inputs = processor(images=image, text="Solve the math problem:", return_tensors="pt")
     
     # Generate the solution
@@ -25,14 +28,13 @@ demo = gr.Interface(
     inputs=gr.Image(type="pil", label="Upload Handwritten Math Problem"),
     outputs=gr.Textbox(label="Solution"),
     title="Handwritten Math Problem Solver",
-    description="Upload an image of a handwritten math problem, and the model will solve it.",
+    description="Upload an image of a handwritten math problem, and the model will attempt to solve it.",
     examples=[
-        ["example1.jpg"],  # Add example images
+        ["example1.jpg"],  # Add example images if available
         ["example2.jpg"]
     ],
     theme="soft"
 )
 
-# Launch the app
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()