fix: filtres Journal de Bord — direction + asset_class tous onglets

Direction (Ouvert) : t.direction n'existe pas dans trade_entry_prices → utilisait
undefined, excluait tout. Remplacé par _isBearishStr(t.strategy) comme Fermés.

Asset class (Ouvert, Fermés, Non loggés) : l'IA retournait parfois "commodities",
"currencies", "fx", "equity" au lieu des clés canoniques. Double correction :
- Frontend : _normalizeAssetClass() mappe les variantes → energy|metals|agriculture|
  indices|equities|forex dans les 3 sections filtrées
- Backend database.py : _normalize_asset_class() appliqué à l'INSERT dans
  trade_entry_prices et skipped_trades (nouveaux trades normalisés au stockage)
- Prompt ai_analyzer.py : suggested_trades[].asset_class contraint à l'enum explicite

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/services/ai_analyzer.py

@@ -1173,14 +1173,14 @@ Retourne UNIQUEMENT ce JSON:
           "strategy": "<Long Call|Long Put|Bull Call Spread|Bear Put Spread|Long Straddle|Iron Condor|Short Strangle|Cash-Secured Put|Covered Call — respecter règles IVR>",
           "underlying": "<ticker Yahoo Finance>",
           "rationale": "<pourquoi ce trade dans ce contexte macro+géo+vol>",
-          "asset_class": "<classe>",
+          "asset_class": "<energy|metals|agriculture|indices|equities|forex>",
           "expected_move_pct": <float, RENDEMENT OPTION en % pour CE trade si thèse confirmée. Long Call: 80-250%, Spread: 40-120%, Straddle: 60-180%.>
         }},
         {{
           "strategy": "<autre stratégie respectant les règles IVR>",
           "underlying": "<ticker Yahoo Finance>",
           "rationale": "<rationale>",
-          "asset_class": "<classe>",
+          "asset_class": "<energy|metals|agriculture|indices|equities|forex>",
           "expected_move_pct": <float, rendement option attendu en % pour ce trade spécifique>
         }}
       ]

backend/services/database.py

@@ -1027,6 +1027,26 @@ def _normalize_yf_ticker(ticker: str) -> str:
     return t
 
 
+def _normalize_asset_class(cls: str) -> str:
+    """Map AI-returned asset_class variants to canonical keys used in the UI."""
+    if not cls:
+        return ""
+    c = cls.lower().strip()
+    if any(k in c for k in ("energy", "oil", "gas", "petrol", "brent", "wti")):
+        return "energy"
+    if any(k in c for k in ("metal", "gold", "silver", "copper", "mining", "precious")):
+        return "metals"
+    if any(k in c for k in ("agri", "grain", "corn", "wheat", "soy", "crop", "coton", "coffee", "cocoa")):
+        return "agriculture"
+    if any(k in c for k in ("index", "indic", "indices", "spx", "nasdaq", "dow", "s&p", "russell", "cac", "dax")):
+        return "indices"
+    if any(k in c for k in ("equit", "stock", "action", "share", "sector", "xle", "xlf", "xlk")):
+        return "equities"
+    if any(k in c for k in ("forex", "currency", "fx", "devise", "change", "eur", "usd", "jpy", "dxy")):
+        return "forex"
+    return c
+
+
 def log_trade_entries(run_id: str, scored_patterns: List[Dict[str, Any]], quotes: Dict[str, Any]):
     """
     For each scored pattern's trade_rankings, record entry price if the trade
@@ -1191,7 +1211,7 @@ def log_trade_entries(run_id: str, scored_patterns: List[Dict[str, Any]], quotes
                 )
                 updated_count += 1
             else:
-                _trade_asset_class = (
+                _trade_asset_class = _normalize_asset_class(
                     trade.get("asset_class") or
                     sp.get("asset_class") or
                     _orig.get("asset_class") or
@@ -1387,7 +1407,7 @@ def log_skipped_trade(run_id: str, pattern_id: str, pattern_name: str,
             expected_move_pct, skip_reason, skip_detail, asset_class)
            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
         (run_id, pattern_id, pattern_name, underlying, strategy, score,
-         expected_move_pct, skip_reason, skip_detail, asset_class)
+         expected_move_pct, skip_reason, skip_detail, _normalize_asset_class(asset_class))
     )
     conn.commit()
     conn.close()