Create app.py

app.py

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+import gradio as gr
+import joblib
+import numpy as np
+
+# Carregar o modelo serializado
+model = joblib.load("tiebreak_model.pkl")
+
+# Função para realizar a previsão
+def predict_tiebreak(win_odds, loser_odds):
+    # Calculando as features
+    odds_ratio = win_odds / loser_odds
+    log_odds_w = np.log(win_odds)
+    log_odds_l = np.log(loser_odds)
+    prob_w = 1 / win_odds
+    prob_l = 1 / loser_odds
+    odds_spread = abs(loser_odds - win_odds)
+
+    # Criando o vetor de features para o modelo
+    features = np.array([[odds_ratio, log_odds_w, log_odds_l, prob_w, prob_l, odds_spread]])
+
+    # Realizando a previsão
+    prob = model.predict_proba(features)[0, 1]  # Probabilidade da classe 1 (menos de 1.5 tiebreaks)
+    
+    # Calculando a odds mínima
+    odds_minima = 1 / prob
+    
+    # Retornando os valores arredondados
+    return round(prob, 2), round(odds_minima, 2)
+
+# Interface Gradio
+inputs = [gr.inputs.Number(label="Win Odds"), gr.inputs.Number(label="Loser Odds")]
+outputs = [gr.outputs.Textbox(label="Probabilidade de menos de 1.5 Tiebreaks"), gr.outputs.Textbox(label="Odds Mínima")]
+
+# Criação da interface
+gr.Interface(fn=predict_tiebreak, inputs=inputs, outputs=outputs, title="Previsão de Tiebreaks",
+             description="Insira as odds de vitória e derrota para prever a probabilidade de haver menos de 1.5 tiebreaks e calcular as odds mínimas.").launch()