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app.py

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+# -*- coding: utf-8 -*-
+import gradio as gr
+import numpy as np
+import pandas as pd
+from sklearn.preprocessing import StandardScaler
+from sklearn.model_selection import train_test_split
+from sklearn import svm
+from sklearn.metrics import accuracy_score
+kkk_diabetes_dataset = pd.read_csv('diabetes.csv') 
+X = kkk_diabetes_dataset.drop(columns = 'Outcome', axis=1)
+Y = kkk_diabetes_dataset['Outcome']
+scaler = StandardScaler()
+scaler.fit(X)
+standardized_data = scaler.transform(X)
+
+X = standardized_data
+Y = kkk_diabetes_dataset['Outcome']
+from sklearn.neural_network import MLPClassifier
+classifier =  MLPClassifier(max_iter=1000,  alpha=1)
+X_train, X_test, Y_train, Y_test = train_test_split(X,Y, test_size = 0.2, stratify=Y, random_state=2)
+classifier.fit(X_train, Y_train)
+
+def diabetes(Pregnancies, Glucose_levels_in_millimoles_per_litres, Blood_Pressure_in_millimetres_of_mercury, Skin_Thickness_in_millimetres, Insulin_levels, BMI_in_kilogram_per_square_metres, Diabetes_Pedigree, Age_in_years):
+    x = np.array([Pregnancies, Glucose_levels_in_millimoles_per_litres, Blood_Pressure_in_millimetres_of_mercury, Skin_Thickness_in_millimetres, Insulin_levels, BMI_in_kilogram_per_square_metres, Diabetes_Pedigree, Age_in_years])
+    prediction = classifier.predict(x.reshape(1, -1))
+    if prediction == 0:
+        return "Patient is NOT DIABETIC"
+    elif prediction == 1:
+        return "Patient is DIABETIC"
+
+outputs = gr.outputs.Textbox()
+app = gr.Interface(fn=diabetes, 
+                   inputs=[gr.inputs.Slider(0,9,step=1,label= 'How many times has the patient been pregnant, 0 if unapplicable'),
+                           'number',
+                           'number',
+                           'number',
+                           'number',
+                           'number',
+                           gr.inputs.Slider(0,1,label= 'Diabetes Pedigree function'),
+                           'number'], 
+                   outputs='text',
+                   theme="grass",
+                   title="kkk's Machine Learning App",
+                   description="This is a diabetes model")
+
+app.launch(inline = False)
+
+

requirements.txt

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+huggingface-hub==0.5.1
+numpy==1.21.6
+torch
+transformers==4.18.0
+pandas==1.3.5
+matplotlib==3.2.2
+scikit-learn==1.0.2