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import gradio as gr
import joblib
import numpy as np
# 模型載入（需確認這些檔案存在於 Hugging Face Space 中）
clf_result = joblib.load("clf_result.pkl")
clf_cov = joblib.load("clf_cov.pkl")
clf_ou = joblib.load("clf_ou.pkl")
clf_score = joblib.load("clf_score.pkl")
score_classes = joblib.load("score_classes.pkl")
def parse_ah(value):
try:
if '/' in value:
parts = value.replace('+', '').split('/')
return round((float(parts[0]) + float(parts[1])) / 2, 2)
else:
return float(value.replace('+', ''))
except:
raise ValueError("❌ 讓球盤格式錯誤，請輸入 0.5 或 +0.5/+1")
def predict_all(B365H, B365D, B365A, Over25, Under25, AHCh, AHH, AHA):
try:
prob_h = 1 / float(B365H)
prob_d = 1 / float(B365D)
prob_a = 1 / float(B365A)
sum_prob = prob_h + prob_d + prob_a
imp_prob_h = prob_h / sum_prob
imp_prob_d = prob_d / sum_prob
imp_prob_a = prob_a / sum_prob
over_prob = 1 / float(Over25)
under_prob = 1 / float(Under25)
over_diff = over_prob - under_prob
ah_diff = float(AHH) - float(AHA)
ah_value = parse_ah(AHCh)
features = [[imp_prob_h, imp_prob_d, imp_prob_a, over_diff, ah_diff, ah_value]]
prob_res = clf_result.predict_proba(features)[0]
pred_res = clf_result.classes_[prob_res.argmax()]
prob_cov = clf_cov.predict_proba(features)[0]
pred_cov = "Covered" if prob_cov[1] >= 0.5 else "Not Covered"
prob_ou = clf_ou.predict_proba(features)[0]
pred_ou = "Over" if prob_ou[1] >= 0.5 else "Under"
prob_score = clf_score.predict_proba(features)[0]
top3_idx = prob_score.argsort()[::-1][:3]
top3_scores = [(score_classes[i], prob_score[i]) for i in top3_idx]
score_text = "\n".join([f"🥇🥈🥉"[i] + f" {s}（{p*100:.1f}％）" for i, (s, p) in enumerate(top3_scores)])
conf = max(prob_res.max(), prob_cov[1], prob_ou[1])
if conf >= 0.7:
confidence = "High"
elif conf >= 0.5:
confidence = "Medium"
else:
confidence = "Low"
return {
"result": pred_res,
"result_prob": round(prob_res.max(), 4),
"handicap": pred_cov,
"handicap_prob": round(max(prob_cov), 4),
"ou": pred_ou,
"ou_prob": round(max(prob_ou), 4),
"confidence": confidence,
"score_top3": top3_scores
}
except Exception as e:
return {"error": str(e)}
demo = gr.Interface(
fn=predict_all,
inputs=[
gr.Textbox(label="主勝賠率 B365H"),
gr.Textbox(label="和局賠率 B365D"),
gr.Textbox(label="客勝賠率 B365A"),
gr.Textbox(label="Over 2.5 賠率"),
gr.Textbox(label="Under 2.5 賠率"),
gr.Textbox(label="讓球盤口（如 +0.5/+1）"),
gr.Textbox(label="主隊讓球賠率 AHH"),
gr.Textbox(label="客隊受讓賠率 AHA"),
],
outputs="json",
title="⚽ 比賽預測 API + UI",
description="輸入盤口與賠率，預測勝負、過盤、大小、正確比分、信心等級",
allow_flagging="never"
)
demo.launch()
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