Upload 3 files

app.py

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+import gradio as gr
+import joblib
+import numpy as np
+
+# Load the model
+model = joblib.load("random_forest_model.pkl")
+
+# Prediction function
+def predict_insulin(age, gender, height, weight, bmi, smoking, alcoholic, dm_years, hba1c, fbs, ppbs):
+    gender = 1 if gender.lower() == "male" else 0
+    smoking = 1 if smoking.lower() == "yes" else 0
+    alcoholic = 1 if alcoholic.lower() == "yes" else 0
+
+    features = np.array([[age, gender, height, weight, bmi, smoking, alcoholic, dm_years, hba1c, fbs, ppbs]])
+    prediction = model.predict(features)[0]
+
+    return "Needs Insulin" if prediction == 1 else "No Insulin Needed"
+
+iface = gr.Interface(
+    fn=predict_insulin,
+    inputs=[
+        gr.Number(label="Age"),
+        gr.Radio(["Male", "Female"], label="Gender"),
+        gr.Number(label="Height (cm)"),
+        gr.Number(label="Weight (kg)"),
+        gr.Number(label="BMI"),
+        gr.Radio(["Yes", "No"], label="Smoking"),
+        gr.Radio(["Yes", "No"], label="Alcoholic"),
+        gr.Number(label="Diabetes Duration (Years)"),
+        gr.Number(label="HbA1c"),
+        gr.Number(label="FBS"),
+        gr.Number(label="PPBS")
+    ],
+    outputs=gr.Text(label="Prediction"),
+    title="Insulin Dependency Predictor"
+)
+
+iface.launch()

random_forest_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5b4daa62fd7160929e783f0b1deafe8087a1a2a1aeee4e536b7250acc6303958
+size 75385

requirements.txt

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+gradio
+scikit-learn
+numpy
+joblib