app.py

import gradio as gr
from huggingface_hub import InferenceClient

def saveData(prompt):
  import csv
  with open('/content/drive/MyDrive/IT 164/prompt.csv', 'a') as f:
    w=csv.writer(f)
    w.writerow([prompt])

def fill_mask(prompt):
  client=InferenceClient()
  input= f"{prompt} <mask>" 
  output=client.fill_mask(input)
  allsentences=''
  for item in output:
    mask=item.token_str
    if mask=='':  break
    sentence=f"{prompt} {mask}"
    allsentences=allsentences+sentence+'\n'
  return (allsentences)

def fill_mask_bert(prompt):
  model_name="FacebookAI/xlm-roberta-base"
  client=InferenceClient(model_name)
  input= f"{prompt} <mask>" 
  output=client.fill_mask(input)
  allsentences=''
  for item in output:
    mask=item.token_str
    if mask=='':  break
    sentence=f"{prompt} {mask}"
    allsentences=allsentences+sentence+'\n'
  return (allsentences)

with gr.Blocks(theme=gr.themes.Citrus()) as demo:
  with gr.Row():
    with gr.Column():
      prompt=gr.Textbox(label="your prompt",scale=1)
    with gr.Column():
      blackforest_btn=gr.Button("fill mask", scale=1)
      text= gr.Text(type="text", label="fill word")
      #sending the prompt to function to get a text
      blackforest_btn.click(fn=fill_mask, inputs=prompt, outputs=text)
    with gr.Column():
      bert_btn=gr.Button("fill mask", scale=1)
      berttext= gr.Text(type="text", label="fill word")
      #sending the prompt to function to get a text
      bert_btn.click(fn=fill_mask_bert, inputs=prompt, outputs=berttext)

demo.launch(debug=True)