from transformers import pipeline
from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
id2label = { 0: "sadness",  1:"joy", 2:"love", 3:"anger", 4:"fear", 5:"surprise" }
label2id = { "sadness":0, "joy":1, "love":2, "anger":3, "fear":4, "surprise":5}
 
 
tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
model = AutoModelForSequenceClassification.from_pretrained("Sadiksha/sentiment_analysis_bert", id2label=id2label, label2id=label2id)
pipe = pipeline('sentiment-analysis', model = model, tokenizer=tokenizer)


import gradio as gr
def predict(text):
  return pipe(text)[0]['label']

iface = gr.Interface(
  fn=predict, 
  inputs='text',
  outputs='text',
  examples=[["I just received an unexpected gift from my friend and it made my day!"],
            ["I am feeling so lonely without my family around during the holidays."],
            ["I have a fear of spiders, they give me the creeps."]]
)

iface.launch()