Update app.py

app.py

@@ -6,6 +6,35 @@ import os
 import joblib
 from model import DualStreamTransformer, ArcMarginProduct
 
+css = """
+.scroll-box {
+    height: 300px;
+    overflow-y: auto !important;
+    overflow-x: hidden !important;
+    display: block !important;
+    width: 100% !important;
+    max-width: 100% !important;
+}
+.scroll-box * {
+    max-width: 100% !important;
+    box-sizing: border-box !important;
+}
+.vertical-radio {
+    display: block !important;
+    width: 100% !important;
+}
+.vertical-radio .wrap {
+    display: flex !important;
+    flex-direction: column !important;
+    width: 100% !important;
+    min-width: 0 !important;
+}
+.vertical-radio .gradio-radio-item {
+    width: 100% !important;
+    white-space: normal !important;
+    word-break: break-all !important;
+}
+"""
 
 DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 FOLD = 5
@@ -40,36 +69,33 @@ def analyze_and_predict(*all_answers):
 
         with torch.no_grad():
             feats = model(sx1, sx2)
+            # 確保 metric_fc 初始化時是 ArcMarginProduct(32, 2)
             logits = metric_fc.predict(feats)
             probs = torch.softmax(logits, dim=1)
             pred_idx = torch.argmax(probs, dim=1).item()
             conf = probs[0, pred_idx].item()
             
-        print(f"DEBUG: Prediction successful! Pred: {pred_idx}")
+        print(f"DEBUG: 推論成功! 索引: {pred_idx}, 信心度: {conf}")
 
-
-        if pred_idx == 1:
-            res_label = "正常 / 健康"
-        elif pred_idx == 0:
+        if pred_idx == 0:
             res_label = "乾眼風險 (DES)"
         else:
             res_label = "修格蘭氏症風險 (SJS)"
 
         prob_dict = {
-            "健康": probs[0, 0].item(),
-            "乾眼 (DES)": probs[0, 1].item(),
-            "修格蘭氏 (SJS)": probs[0, 2].item()
+            "乾眼 (DES)": probs[0, 0].item(),
+            "修格蘭氏 (SJS)": probs[0, 1].item()
         }
-        
+
         return (
             f"## 診斷結果：{res_label}",
-            f"**分析完成**：AI 信心度為 **{conf:.2%}**。本系統整合了中醫 24 項體質特徵與西醫 10 項 OSDI 症狀進行多模態計算。",
-            {"Risk": conf if pred_idx==1 else 1-conf, "Healthy": 1 - (conf if pred_idx==1 else 1-conf)}
+            f"**分析完成**：AI 信心度為 **{conf:.2%}**。本系統已整合 CCMQ 體質與 OSDI 症狀進行二分類篩檢。",
+            prob_dict
         )
 
     except Exception as e:
-        print(f"Error: {e}")
-        return f"### 計算出錯", str(e), {}
+            print(f"計算出錯: {e}")
+            return "### 計算出錯", f"錯誤原因: {str(e)}", {}
 
 with gr.Blocks(theme=gr.themes.Soft(), css=".scroll-box { height: 400px; overflow-y: auto; border: 1px solid #ddd; padding: 15px; border-radius: 8px; }") as demo:
     gr.Markdown("# 中西醫 AI 診斷系統")
@@ -91,7 +117,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=".scroll-box { height: 400px; overflo
                     
                     with gr.Row():
                         back_btn = gr.Button("返回")
-                        submit_btn = gr.Button("🚀 生成分析報告", variant="primary")
+                        submit_btn = gr.Button(" 生成分析報告", variant="primary")
 
 
         with gr.Column(scale=1):