fix: OOM-safe SQL filtering + relevance scoring for /api/chat

Problem: On every chat request, ALL 1015 aussteller + 1861 neuheiten rows
were loaded into Python (2876 rows × full-text processing). Multiple
concurrent requests caused OOM kills (exit 137).

Fix:
- SQL LIKE filtering with parameterized queries (WHERE ... OR ... LIMIT 30)
- Relevance scoring in SQL: longer search terms = higher weight
- Tokenization: re.findall strips punctuation ('kosmos?' → 'kosmos')
- Stopword filtering removes noise ('die', 'hat', etc.)
- Removed duplicate 'gibt' in stopwords

Verified: Kosmos, Asmodee (6 Stände), Pegasus (3 Stände), Flip & Write

app.py

@@ -3105,35 +3105,65 @@ def api_chat():
             + (f" | von {name}" if name else '')
         )
 
-    # Also search aussteller table for matching exhibitors
+    # Also search aussteller table using SQL LIKE filters (OOM-safe)
-    search_terms = user_message.lower().split()
+    # Extract alphanumeric+umlaut tokens (strip punctuation like '?', '!', ',')
+    search_terms = re.findall(r'[a-z0-9äöüß]+', user_message.lower())
+    # Filter stopwords to reduce noise
+    stopwords = {'die', 'der', 'das', 'und', 'ist', 'ein', 'eine', 'den', 'dem', 'des',
+                 'mit', 'auf', 'für', 'von', 'zu', 'im', 'in', 'an', 'es', 'nicht',
+                 'ich', 'wir', 'sie', 'er', 'was', 'wo', 'wie', 'welche', 'welcher',
+                 'welches', 'gibt', 'noch', 'mehr', 'alle', 'oder', 'auch'}
+    meaningful_terms = [t for t in search_terms if t not in stopwords and len(t) > 1]
+    
+    # Build SQL LIKE filter for aussteller with relevance scoring
     aussteller_rows = []
-    try:
+    if meaningful_terms:
-        aussteller_rows = db.execute(
+        # Build score expression: longer terms = higher weight
-            "SELECT name, halle, stand, land, info, web, themen FROM aussteller LIMIT 1015"
+        score_parts = []
-        ).fetchall()
+        like_clauses = []
-    except Exception:
+        params = []
-        aussteller_rows = []
+        for t in meaningful_terms:
+            term_len = len(t)
+            score_parts.append(
+                f"(CASE WHEN LOWER(name) LIKE ? OR LOWER(halle) LIKE ? OR LOWER(stand) LIKE ? "
+                f"OR LOWER(land) LIKE ? OR LOWER(info) LIKE ? OR LOWER(themen) LIKE ? THEN {term_len} ELSE 0 END)"
+            )
+            like_clauses.append(
+                "(LOWER(name) LIKE ? OR LOWER(halle) LIKE ? OR LOWER(stand) LIKE ? "
+                "OR LOWER(land) LIKE ? OR LOWER(info) LIKE ? OR LOWER(themen) LIKE ?)"
+            )
+            # Push params: first 6 for scoring, then 6 for WHERE
+            params.extend([f'%{t}%'] * 6)
+        # Re-add WHERE params after score params
+        params.extend(params[:])  # duplicate for WHERE clause
+        score_expr = ' + '.join(score_parts)
+        sql = (
+            f"SELECT name, halle, stand, land, info, web, themen, ({score_expr}) AS relevance "
+            "FROM aussteller "
+            f"WHERE {' OR '.join(like_clauses)} "
+            "ORDER BY relevance DESC LIMIT 30"
+        )
+        try:
+            aussteller_rows = db.execute(sql, params).fetchall()
+        except Exception:
+            aussteller_rows = []
 
     if aussteller_rows:
-        # Score and filter exhibitors by keyword match
+        # Score and filter exhibitors by keyword match (already SQL-filtered)
         scored = []
         for a in aussteller_rows:
             full_text = f"{a['name'] or ''} {a['halle'] or ''} {a['stand'] or ''} {a['land'] or ''} {a['info'] or ''} {a['themen'] or ''}".lower()
-            score = sum(1 for t in search_terms if t in full_text)
+            score = sum(1 for t in meaningful_terms if t in full_text)
-            if score > 0:
+            scored.append((score, a))
-                scored.append((score, a))
         scored.sort(key=lambda x: -x[0])
         # Merge exhibitors with similar names (case-insensitive substring match)
         merged = {}
         merge_order = []
         for score, a in scored:
             name_lower = (a['name'] or '').strip().lower()
-            # Find existing merge target
             found = False
             for existing_name in merge_order:
                 if name_lower in existing_name or existing_name in name_lower:
-                    # Merge stands
                     existing_stands = merged[existing_name]['stand']
                     new_stands = (a['stand'] or '').strip()
                     all_stands = set(s.strip() for s in (existing_stands + '|' + new_stands).split('|') if s.strip())
@@ -3146,10 +3176,8 @@ def api_chat():
                 merged[name_lower]['stand'] = (a['stand'] or '').strip()
                 merged[name_lower]['_score'] = score
         
-        # Replace scored with merged entries
         new_scored = [(merged[n]['_score'], merged[n]) for n in merge_order]
         new_scored.sort(key=lambda x: -x[0])
-        # Add top matching exhibitors
         for _, a in new_scored[:20]:
             stands_raw = (a['stand'] or '').strip()
             stands_list = [s.strip() for s in stands_raw.split('|') if s.strip()]
@@ -3164,36 +3192,45 @@ def api_chat():
                 + (f" | {info}" if info else '')
                 + (f" | Web: {web}" if web else '')
             )
-        # Also include all exhibitors matching the user's search when they ask about halls/stands
+
-        if any(t in user_message.lower() for t in ['halle', 'stand', 'aussteller', 'verlag', 'verlage', 'publisher', 'spiel']):
+    # Search neuheiten table using SQL LIKE filters with relevance scoring (OOM-safe)
-            for _, a in new_scored[:40]:
-                stands_raw = (a['stand'] or '').strip()
-                stands_list = [s.strip() for s in stands_raw.split('|') if s.strip()]
-                halle_stand = ' | '.join(stands_list) if len(stands_list) > 1 else (stands_list[0] if stands_list else '')
-                land = a['land'] or ''
-                context_parts.append(
-                    f"[Aussteller] {a['name']}"
-                    + (f" | {halle_stand}" if halle_stand else '')
-                    + (f" | {land}" if land else '')
-                )
-    # Also search neuheiten table for matching games
     neuheiten_rows = []
-    try:
+    if meaningful_terms:
-        neuheiten_rows = db.execute(
+        score_parts_n = []
-            "SELECT titel, untertitel, halle, stand, info_text, themen, web FROM neuheiten LIMIT 1861"
+        like_clauses_n = []
-        ).fetchall()
+        params_n = []
-    except Exception:
+        for t in meaningful_terms:
-        neuheiten_rows = []
+            term_len = len(t)
+            score_parts_n.append(
+                f"(CASE WHEN LOWER(titel) LIKE ? OR LOWER(untertitel) LIKE ? OR LOWER(halle) LIKE ? "
+                f"OR LOWER(stand) LIKE ? OR LOWER(info_text) LIKE ? OR LOWER(themen) LIKE ? THEN {term_len} ELSE 0 END)"
+            )
+            like_clauses_n.append(
+                "(LOWER(titel) LIKE ? OR LOWER(untertitel) LIKE ? OR LOWER(halle) LIKE ? "
+                "OR LOWER(stand) LIKE ? OR LOWER(info_text) LIKE ? OR LOWER(themen) LIKE ?)"
+            )
+            params_n.extend([f'%{t}%'] * 6)
+        params_n.extend(params_n[:])  # duplicate for WHERE clause
+        score_expr_n = ' + '.join(score_parts_n)
+        sql_n = (
+            f"SELECT titel, untertitel, halle, stand, info_text, themen, web, ({score_expr_n}) AS relevance "
+            "FROM neuheiten "
+            f"WHERE {' OR '.join(like_clauses_n)} "
+            "ORDER BY relevance DESC LIMIT 30"
+        )
+        try:
+            neuheiten_rows = db.execute(sql_n, params_n).fetchall()
+        except Exception:
+            neuheiten_rows = []
 
     if neuheiten_rows:
         scored_n = []
         for n in neuheiten_rows:
             full_text = f"{n['titel'] or ''} {n['untertitel'] or ''} {n['halle'] or ''} {n['stand'] or ''} {n['info_text'] or ''} {n['themen'] or ''}".lower()
-            score = sum(1 for t in search_terms if t in full_text)
+            score = sum(1 for t in meaningful_terms if t in full_text)
             if score > 0:
                 scored_n.append((score, n))
         scored_n.sort(key=lambda x: -x[0])
-        # Add top matching games
         for _, n in scored_n[:20]:
             halle_stand = f"{n['halle'] or ''} {n['stand'] or ''}".strip()
             verlag = n['untertitel'] or ''
@@ -3204,16 +3241,6 @@ def api_chat():
                 + (f" | {halle_stand}" if halle_stand else '')
                 + (f" | {themen}" if themen else '')
             )
-        # For game/neuheit-specific queries, add more results
-        if any(t in user_message.lower() for t in ['neuheit', 'neuheiten', 'spiel', 'spiele', 'brettspiel', 'kartenspiel', 'würfelspiel', 'game', 'neu']):
-            for _, n in scored_n[:40]:
-                halle_stand = f"{n['halle'] or ''} {n['stand'] or ''}".strip()
-                verlag = n['untertitel'] or ''
-                context_parts.append(
-                    f"[Neuheit] {n['titel']}"
-                    + (f" | Verlag: {verlag}" if verlag else '')
-                    + (f" | {halle_stand}" if halle_stand else '')
-                )
     context = '\n'.join(context_parts)
 
     # System prompt