Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+from xgboost import Booster, DMatrix
+import numpy as np
+
+# Define the mapping of card names to IDs (placeholder example)
+card_numbers = {
+    "Card 1": 1,
+    "Card 2": 2,
+    "Card 3": 3,
+    "Card 4": 4,
+    "Card 5": 5,
+    "Card 6": 6,
+    "Card 7": 7,
+    "Card 8": 8,
+    # Add all 181 cards here...
+}
+
+MODEL_PATH = "clash_royale_model/model.json"
+
+def deck_to_ids(deck, mapping):
+    """Convert card names to IDs based on the mapping."""
+    return [mapping.get(card, 0) - 1 for card in deck]  # Zero-based indices
+
+def preprocess_deck(deck):
+    """Prepare the selected deck for the model."""
+    # Convert cards to IDs
+    deck_ids = deck_to_ids(deck, card_numbers)
+
+    # Perform one-hot encoding
+    num_choices = 181  # Total number of cards
+    one_hot = np.zeros(num_choices, dtype=int)
+    one_hot[np.array(deck_ids)] = 1  # Set 1 for selected cards
+
+    # Add additional features (placeholder for now)
+    trophy_difference = 0  # Placeholder for trophy difference
+    elixir_leaked = 0  # Placeholder for leaked elixir
+
+    # Combine features
+    features = np.concatenate(([trophy_difference, elixir_leaked], one_hot))
+    return pd.DataFrame([features])
+
+def load_model(model_path):
+    """Load the saved XGBoost model."""
+    model = Booster()
+    model.load_model(model_path)
+    return model
+
+# Load the model at startup
+model = load_model(MODEL_PATH)
+
+def predict_outcome(opponent_deck):
+    """Make a prediction based on the opponent's deck."""
+    # Prepare the opponent deck data
+    deck_data = preprocess_deck(opponent_deck)
+
+    # Make the prediction
+    dmatrix = DMatrix(deck_data)  # Convert data to DMatrix format
+    prediction = model.predict(dmatrix)
+
+    # Interpret the prediction
+    result = f"Probability of Winning: {prediction[0] * 100:.2f}%"
+    return result
+
+# List of cards for selection
+card_list = list(card_numbers.keys())
+
+# Create the Gradio interface
+with gr.Blocks() as interface:
+    gr.Markdown("## Clash Royale Prediction")
+    gr.Markdown("Select the 8 cards from the opponent's deck to predict the probability of winning!")
+    
+    opponent_deck = gr.CheckboxGroup(
+        choices=card_list,
+        label="Select 8 cards from the opponent's deck:",
+        info="Select exactly 8 cards."
+    )
+    
+    result = gr.Textbox(label="Prediction Result:", interactive=False)
+
+    def validate_and_predict(deck):
+        """Validate the number of selected cards and make a prediction."""
+        if len(deck) != 8:
+            return "Error: Select exactly 8 cards."
+        return predict_outcome(deck)
+    
+    predict_button = gr.Button("Make Prediction")
+    predict_button.click(validate_and_predict, inputs=[opponent_deck], outputs=[result])
+
+# Launch the interface
+interface.launch()