Create app.py

app.py

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+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()