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import gradio as gr
import pandas as pd
import joblib
scaler = joblib.load("scaler.pkl")
pca = joblib.load("pca.pkl")
kmeans = joblib.load("kmeans_model.pkl")
USER_CREDENTIALS = {
"admin": "password123",
"user": "user123"
}
def login(username, password):
if username in USER_CREDENTIALS and USER_CREDENTIALS[username] == password:
return True, f"Welcome, {username}! Go to Cluster Prediction."
else:
return False, "Incorrect username or password."
def predict_cluster(
Alcohol, Malic_Acid, Ash, Ash_Alcanity, Magnesium,
Total_Phenols, Flavanoids, Nonflavanoid_Phenols,
Proanthocyanins, Color_Intensity, Hue, OD280, Proline
):
data = pd.DataFrame([{
'Alcohol': Alcohol,
'Malic_Acid': Malic_Acid,
'Ash': Ash,
'Ash_Alcanity': Ash_Alcanity,
'Magnesium': Magnesium,
'Total_Phenols': Total_Phenols,
'Flavanoids': Flavanoids,
'Nonflavanoid_Phenols': Nonflavanoid_Phenols,
'Proanthocyanins': Proanthocyanins,
'Color_Intensity': Color_Intensity,
'Hue': Hue,
'OD280': OD280,
'Proline': Proline
}])
X_scaled = scaler.transform(data)
X_pca = pca.transform(X_scaled)
cluster = kmeans.predict(X_pca)[0]
return f"Predicted Cluster: {cluster}"
with gr.Blocks() as app:
with gr.Tab("Login"):
gr.Markdown("## Wine Cluster Prediction - Login")
username = gr.Textbox(label="Username")
password = gr.Textbox(label="Password", type="password")
login_btn = gr.Button("Login")
login_output = gr.Textbox(label="Login Status", interactive=False)
with gr.Tab("Cluster Prediction") as cluster_tab:
gr.Markdown("## Enter Wine Features")
with gr.Row():
Alcohol_in = gr.Number(label="Alcohol")
Malic_Acid_in = gr.Number(label="Malic Acid")
Ash_in = gr.Number(label="Ash")
Ash_Alcanity_in = gr.Number(label="Ash Alcanity")
Magnesium_in = gr.Number(label="Magnesium")
with gr.Row():
Total_Phenols_in = gr.Number(label="Total Phenols")
Flavanoids_in = gr.Number(label="Flavanoids")
Nonflavanoid_Phenols_in = gr.Number(label="Nonflavanoid Phenols")
Proanthocyanins_in = gr.Number(label="Proanthocyanins")
with gr.Row():
Color_Intensity_in = gr.Number(label="Color Intensity")
Hue_in = gr.Number(label="Hue")
OD280_in = gr.Number(label="OD280")
Proline_in = gr.Number(label="Proline")
predict_btn = gr.Button("Predict Cluster")
cluster_output = gr.Textbox(label="Cluster Result", interactive=False)
login_btn.click(
fn=login,
inputs=[username, password],
outputs=[gr.State(), login_output]
)
predict_btn.click(
fn=predict_cluster,
inputs=[
Alcohol_in, Malic_Acid_in, Ash_in, Ash_Alcanity_in, Magnesium_in,
Total_Phenols_in, Flavanoids_in, Nonflavanoid_Phenols_in,
Proanthocyanins_in, Color_Intensity_in, Hue_in, OD280_in, Proline_in
],
outputs=[cluster_output]
)
app.launch()
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