import gradio as gr
import os 
import numpy as np 
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from sklearnex import patch_sklearn, unpatch_sklearn
patch_sklearn()
import xgboost as xgb
import keras_nlp
preprocessor = keras_nlp.models.GemmaPreprocessor.from_preset(
    "gemma_2b_en", sequence_length=64
)
model = keras_nlp.models.GemmaBackbone.from_preset("gemma_2b_en")


def greet(name):
  x = preprocessor(name)
  lab = model(x)
  return lab

iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch()