app.py

import gradio as gr
from transformers import pipeline
pipe=pipeline('sentiment-analysis','alibidaran/Symptom2disease')
label_2id={'Psoriasis': 0,
'Varicose Veins': 1,
'Typhoid': 2,
'Chicken pox': 3,
'Impetigo': 4,
'Dengue': 5,
'Fungal infection': 6,
'Common Cold': 7,
'Pneumonia': 8,
'Dimorphic Hemorrhoids': 9,
'Arthritis': 10,
'Acne': 11,
'Bronchial Asthma': 12,
'Hypertension': 13,
'Migraine': 14,
'Cervical spondylosis': 15,
'Jaundice': 16,
'Malaria': 17,
'urinary tract infection': 18,
'allergy': 19,
'gastroesophageal reflux disease': 20,
'drug reaction': 21,
'peptic ulcer disease': 22,
'diabetes': 23}
id2_label={f'LABEL_{i}':v for v,i in label_2id.items()}
def detect_symptom(symptoms):
  output=pipe(symptoms)[0]
  label=id2_label[output['label']]
  return f"You have {label} disease."

demo=gr.Interface(fn=detect_symptom,inputs='text',outputs='label')
demo.launch()