app.py

import gradio as gr
from huggingface_hub import from_pretrained_keras

# Load the model from Hugging Face Hub
model = from_pretrained_keras("Bajiyo/Malayalam_transliteration")

# Function to preprocess text (replace with model-specific preprocessing if needed)
def preprocess_text(input_text):
  # Assuming character-level model: convert text to sequence of integer indices
  # Replace with your specific preprocessing steps based on the model's requirements
  # You might need tokenization or other transformations
  # ...
  return preprocessed_text

def transliterate(input_text):
  # Preprocess the input text
  preprocessed_text = preprocess_text(input_text)

  # Make predictions using the model
  predictions = model.predict(preprocessed_text)

  # Post-process the predictions if needed (replace with your logic)
  output_text = predictions  # Assuming model outputs transliteration directly

  return output_text

textbox = gr.inputs.Textbox(label="Enter Malayalam Text")

demo = gr.Interface(fn=transliterate,
                    inputs=textbox,
                    outputs=gr.outputs.Textbox(label="Transliteration to English"),
                    title="Malayalam to English Transliteration"
                    )

demo.launch()