import gradio as gr
from transformers import pipeline
from transformers import AutoModelForCausalLM, AutoTokenizer

def generateYodaLanguage(prompt):
  repo_id="dvgodoy/phi3-mini-yoda-adapter"
  model = AutoModelForCausalLM.from_pretrained (repo_id)
  tokenizer = AutoTokenizer.from_pretrained(repo_id)
  generator = pipeline("text-generation", model=repo_id)
  output = generator([{"role": "user", "content": prompt}], max_new_tokens=128, return_full_text=False)[0]
  return output["generated_text"]

with gr.Blocks() as demo:
  with gr.Row():
    text=gr.Textbox(label="prompt")
    translate_btn=gr.Button("Say it in Yoda Language!")
    output=gr.Textbox(label="Yoda language")
    translate_btn.click(fn=generateYodaLanguage, inputs=text, outputs=output)
demo.launch(debug=True,share=True)