app.py

# now to create an interface with gradio
import gradio as gr
from transformers import pipeline

from gradio_space_ci import enable_space_ci

enable_space_ci()



pipe = pipeline("text2text-generation", model="google/flan-t5-base")

# a function that uses the pipeline
# takes text as input and passes it to the pipeline
def chat(text):
  output = pipe(text)[0]["generated_text"]
  return output
#                   fucntion , input of type text , output of type text
demo = gr.Interface(chat     , "text"             ,   "text" )
demo.launch()