Update dashboard.py

dashboard.py

@@ -13,18 +13,19 @@ REQUIRED_COLS = [
     "impressions","clicks","conversions","cost","features_json"
 ]
 
-# ---- helpers ----
-def _ok(msg: str):
-    return gr.Markdown.update(value=f"✅ {msg}")
-def _warn(msg: str):
-    return gr.Markdown.update(value=f"⚠️ {msg}")
-def _err(msg: str):
-    return gr.Markdown.update(value=f"❌ {msg}")
-
-# ---- data ops ----
+# ---------- helpers ----------
+def _ok(msg: str) -> str:
+    return f"✅ {msg}"
+def _warn(msg: str) -> str:
+    return f"⚠️ {msg}"
+def _err(msg: str) -> str:
+    return f"❌ {msg}"
+
+# ---------- data ops ----------
 def ui_refresh_tables():
     df = read_events()
     agg = aggregate()
+    # 3つ目の出力（status）は Markdown なので、単なる文字列でOK
     return df, agg, _ok("Refreshed.")
 
 def ui_load_sample():
@@ -45,30 +46,42 @@ def ui_load_sample():
     return df, agg, _ok("Sample data loaded.")
 
 def ui_upload_csv(file: gr.File):
+    # アウトプットは [grid, grid_agg, status]
     if file is None:
+        # 表は変更しない → gr.update() で“no change”、statusだけ文字列更新
         return gr.update(), gr.update(), _warn("CSVファイルを選択してください。")
     try:
-        df = pd.read_csv(file.name)
+        # 文字コードの揺れに対処
+        try:
+            df = pd.read_csv(file.name)
+        except Exception:
+            df = pd.read_csv(file.name, encoding="utf-8-sig")
     except Exception as e:
         return gr.update(), gr.update(), _err(f"CSV読み込みに失敗: {e}")
 
+    # 区切り子の誤検知（TSV等）を簡易補正
+    if df.shape[1] == 1 and "," in str(df.columns[0]):
+        try:
+            df = pd.read_csv(file.name, sep=",", engine="python")
+        except Exception:
+            pass
+
     missing = [c for c in REQUIRED_COLS if c not in df.columns]
     if missing:
         return gr.update(), gr.update(), _err(f"必須列が不足: {missing}")
 
-    # 型のサニタイズ（軽く）
+    # 軽いサニタイズ
     for c in ["is_control","impressions","clicks","conversions"]:
         df[c] = df[c].fillna(0).astype(int)
-    if "cost" in df.columns:
-        df["cost"] = df["cost"].fillna(0.0).astype(float)
-    if "features_json" in df.columns:
-        df["features_json"] = df["features_json"].fillna("{}").astype(str)
+    df["cost"] = df.get("cost", 0.0)
+    df["cost"] = df["cost"].fillna(0.0).astype(float)
+    df["features_json"] = df.get("features_json", "{}").fillna("{}").astype(str)
 
     append_events(df)
     df2, agg2 = read_events(), aggregate()
     return df2, agg2, _ok(f"取り込み完了（{len(df)}行）。")
 
-# ---- bandit / causal ----
+# ---------- bandit / causal ----------
 def ui_recommend():
     agg = aggregate()
     if agg.empty:
@@ -93,13 +106,13 @@ def ui_fit_uplift():
         return {"message": "No data"}
     return fit_uplift_binary(agg)
 
-# ---- UI ----
+# ---------- UI ----------
 def build_ui():
     with gr.Blocks(title="AdCopy MAB Optimizer Pro") as demo:
         gr.Markdown("# AdCopy MAB Optimizer Pro — Hierarchical TS + Uplift")
 
         with gr.Tab("Data"):
-            status = gr.Markdown()  # メッセージ表示
+            status = gr.Markdown("")  # ← ここは“文字列”を受け取れる
             with gr.Row():
                 btn_refresh = gr.Button("Refresh")
                 btn_seed = gr.Button("Load Sample Data")