import gradio as gr from transformers import pipeline # Initialize the pipeline pipe = pipeline("visual-question-answering", model="openbmb/MiniCPM-Llama3-V-2_5", trust_remote_code=True) # Define the Gradio components image = gr.Image(type="pil", label="Image") question = gr.Textbox(value="Using the standard 9x9 sudoku format, solve the sudoku puzzle in the image correctly.", label="Question") answer = gr.Textbox(label="Answer", show_label=True, show_copy_button=True) title = "Sudoku Solver by FG" description = "Sudoku Solver using MiniCPM-Llama3-V-2_5" # Define the function for solving Sudoku def solve_sudoku(image, question): result = pipe(image, question) return result[0]['answer'] # Create the Gradio interface demo = gr.Interface( fn=solve_sudoku, inputs=[image, question], outputs=answer, title=title, description=description, theme="compact", ) # Launch the interface demo.launch(share=True)