from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline
sa= pipeline("sentiment-analysis")

def adjust(x):
  if x<0:
    return 2*x+1
  return 2*x-1

def sa2(s):
  res= sa(s)
  return [adjust(-1*r['score']) if r['label']=='negative' else adjust(r['score']) for r in res ]
  
  
import pandas as pd

import matplotlib.pyplot as plt
def grfunc(comments):
  df=pd.DataFrame()
  c2=[s.strip() for s in comments.split("\n") if len(s.split())>2]
  df["scores"]= sa2(c2)
  df.plot(kind='hist')
  return plt.gcf()
 
import gradio as gr

iface = gr.Interface(
  fn=grfunc, 
  inputs=gr.inputs.Textbox(placeholder="put your sentences line by line", lines=5), 
  outputs="plot")
iface.launch()