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app.py

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+import gradio as gr
+import joblib
+import numpy as np
+# Load models
+model_flavor = joblib.load("random_forest_model_flavor.pkl")
+model_topping = joblib.load("random_forest_model_topping.pkl")
+model_drink = joblib.load("random_forest_model_drink.pkl")
+
+# Load encoders
+encoder_flavor = joblib.load("encoder_flavor.pkl")
+encoder_topping = joblib.load("encoder_topping.pkl")
+encoder_drink = joblib.load("encoder_drink.pkl")
+input_encoders = joblib.load("input_encoders.pkl")
+
+# Prediction function
+def predict_merienda(mood, weather, craving_level, last_meal, budget):
+    features = [mood, weather, craving_level, last_meal, budget]
+    encoded = [input_encoders[col].transform([val])[0] for col, val in zip(input_encoders.keys(), features)]
+    encoded_np = np.array(encoded).reshape(1, -1)
+    pred_flavor = encoder_flavor.inverse_transform(model_flavor.predict(encoded_np))[0]
+    pred_topping = encoder_topping.inverse_transform(model_topping.predict(encoded_np))[0]
+    pred_drink = encoder_drink.inverse_transform(model_drink.predict(encoded_np))[0]
+    return pred_flavor, pred_topping, pred_drink
+
+# Dropdown options
+mood_list = input_encoders["mood"].classes_.tolist()
+weather_list = input_encoders["weather"].classes_.tolist()
+craving_list = input_encoders["craving_level"].classes_.tolist()
+last_meal_list = input_encoders["last_meal"].classes_.tolist()
+budget_list = input_encoders["budget"].classes_.tolist()
+# Gradio Interface
+iface = gr.Interface(
+    fn=predict_merienda,
+    inputs=[
+        gr.Dropdown(mood_list, label="Mood"),
+        gr.Dropdown(weather_list, label="Weather"),
+        gr.Dropdown(craving_list, label="Craving Level"),
+        gr.Dropdown(last_meal_list, label="Last Meal"),
+        gr.Dropdown(budget_list, label="Budget"),
+    ],
+    outputs=[
+        gr.Text(label="Recommended Flavor"),
+        gr.Text(label="Recommended Topping"),
+        gr.Text(label="Recommended Drink"),
+    ],
+    title=" Merienda Classifier",
+    description="Predicts the best pancit canton flavor, topping, and drink based on your current situation"
+    )
+
+iface.launch()

encoder_drink.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a51dbe23091e1c720ae106f50a6c11eb437eceecfd08bdd1ea9b50a684bc9714
+size 560

encoder_flavor.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e48386a93abacc281d0be9271235411a248960ddb33120067299012e32beea89
+size 594

encoder_topping.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:dec3f14ffe95d20902b4575630f61c8276a8a9537fdd41cbc0f265c9064384b6
+size 563

input_encoders.pkl

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+oid sha256:695f76247033661a613c1da75ebcc6fb27854c52f5e8215fa9899cd685986864
+size 1856

random_forest_model_drink.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:13ae7cf3a611ed9ec50c79716481b8f8253ee060b6743ba85d9c3399a98eff1c
+size 8481105

random_forest_model_flavor.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e572b8564b02f822d32a8f3c68c1544a3ce24cb3f98cc17d302ccba905a015b1
+size 10586497

random_forest_model_topping.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ca163d8c571c79cac7316304cc9e4d424fe23fa99a14393116e59b12f6a95e1d
+size 8121889