from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr
model_ckpt = "booba-uz/english-uzbek-translation_v1"
tokenizer = AutoTokenizer.from_pretrained(model_ckpt)
model = AutoModelForSeq2SeqLM.from_pretrained(model_ckpt)
tokenizer.src_lang = "en"
tokenizer.tgt_lang = "uz"
def translator(input_text):  
    if not input_text.strip():
      return "Iltimos Gap kiriting"
    inputs = tokenizer(input_text, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=256)
    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return translated_text
demo = gr.Interface(
    fn=translator, 
    inputs="text", 
    outputs="text",
)

demo.launch(debug=True)