import gradio as gr from ai4bharat.transliteration import XlitEngine # Function for transliteration def transliterate_to_kashmiri(user_input): # Create an instance of the transliteration engine e = XlitEngine(src_script_type="en", beam_width=5, rescore=False) # Adjusted beam_width for faster performance # Perform transliteration out = e.translit_sentence(user_input, lang_code="ks") return out # Examples for display in the interface examples = [ ["Hello, how are you?", "ہیلؤ، ہاؤ آر یو؟"], ["Good morning!", "گڈ مارننگ!"], ["What is your name?", "تُہند ناو کِیہ چھ؟"], ["I am feeling great today!", "آج سچِہ زبردست ہوں!"], ["See you later!", "بَعِد چُھٹ چھُ؟"] ] # Path to your before and after image files before_image_path = "https://cdn-uploads.huggingface.co/production/uploads/66afb3f1eaf3e876595627bf/cPHY7iEpErxAEakPBWvKR.png" # Replace with actual path to your "before" image after_image_path = "https://cdn-uploads.huggingface.co/production/uploads/66afb3f1eaf3e876595627bf/TZNNe4XJcO4qzoFfug18v.png" # Replace with actual path to your "after" image # Set up the Gradio interface with gr.Blocks() as demo: gr.Markdown(""" # English to Kashmiri Transliteration This tool allows you to convert English sentences into Kashmiri transliterations. **How to use:** 1. Enter a sentence in English in the text box. 2. Click "Transliterate" to see the Kashmiri output. """) # Display the examples gr.Markdown("### Enter your own sentence:") # Create input field for user sentence user_input = gr.Textbox(label="Enter the sentence in English:", placeholder="e.g., Hello, how are you?") # Output area for transliterated text transliterated_output = gr.Textbox(label="Transliterated Output (Kashmiri):", placeholder="Result will be shown here") # Button to trigger the transliteration submit_button = gr.Button("Transliterate") # Define the button action submit_button.click(fn=transliterate_to_kashmiri, inputs=user_input, outputs=transliterated_output) # Add examples to the interface for easy testing gr.Examples(examples=examples, inputs=user_input, outputs=transliterated_output) # Display the "Before" and "After" images with gr.Row(): gr.Image(before_image_path, label="Before", elem_id="before-image", show_label=True) gr.Image(after_image_path, label="After", elem_id="after-image", show_label=True) # Launch the Gradio interface demo.launch(share=True, inbrowser=True)