fix: make recommendation engine robust and prioritize recommendations in dashboard

backend/app/routers/tenders.py

@@ -111,29 +111,39 @@ async def get_recommended_tenders(db: Session = Depends(get_db)):
         return db.query(TenderModel).order_by(TenderModel.closing_date.asc()).limit(5).all()
     
     try:
-        keywords = json.loads(profile.keywords)
+        if profile.keywords.startswith("["):
+            keywords = json.loads(profile.keywords)
+        else:
+            keywords = [kw.strip() for kw in profile.keywords.split(",") if kw.strip()]
     except:
         keywords = [profile.keywords] if profile.keywords else []
 
-    if not keywords:
-        return db.query(TenderModel).order_by(TenderModel.closing_date.asc()).limit(5).all()
+    # Si no hay keywords útiles, devolver las 10 más recientes como sugerencia
+    if not keywords or (len(keywords) == 1 and not keywords[0]):
+        return db.query(TenderModel).order_by(TenderModel.closing_date.desc()).limit(10).all()
 
-    # Construir búsqueda por keywords
+    # Construir búsqueda por keywords (Case-insensitive LIKE)
     filters = []
     for kw in keywords:
-        if len(kw) < 3: continue
-        filters.append(TenderModel.name.ilike(f"%{kw}%"))
-        filters.append(TenderModel.description.ilike(f"%{kw}%"))
-        filters.append(TenderModel.sector.ilike(f"%{kw}%"))
+        if len(kw) < 2: continue
+        search_term = f"%{kw}%"
+        filters.append(TenderModel.name.ilike(search_term))
+        filters.append(TenderModel.description.ilike(search_term))
+        filters.append(TenderModel.buyer.ilike(search_term))
+        filters.append(TenderModel.sector.ilike(search_term))
 
     if not filters:
-        return db.query(TenderModel).order_by(TenderModel.closing_date.asc()).limit(5).all()
+        return db.query(TenderModel).order_by(TenderModel.closing_date.desc()).limit(10).all()
 
-    recommended = db.query(TenderModel).filter(or_(*filters)).order_by(TenderModel.closing_date.asc()).limit(10).all()
+    # Ejecutar búsqueda por relevancia
+    recommended = db.query(TenderModel).filter(or_(*filters)).order_by(TenderModel.closing_date.desc()).limit(15).all()
     
-    # If not enough results, add some newest ones to fill
-    if len(recommended) < 5:
-        more = db.query(TenderModel).order_by(TenderModel.closing_date.asc()).limit(5 - len(recommended)).all()
+    # Si no hay matches específicos, rellenar con las más recientes
+    if not recommended:
+        recommended = db.query(TenderModel).order_by(TenderModel.closing_date.desc()).limit(10).all()
+    elif len(recommended) < 5:
+        existing_ids = [r.id for r in recommended]
+        more = db.query(TenderModel).filter(TenderModel.id.not_in(existing_ids)).order_by(TenderModel.closing_date.desc()).limit(5).all()
         recommended.extend(more)
 
     return recommended

frontend/components/Dashboard.tsx

@@ -315,8 +315,8 @@ export default function Dashboard({
           IA Recommendations for your Company
         </h3>
         <div className="space-y-3">
-          {(tenders.length > 0 || recommendations.length > 0) ? (
-            (tenders.length > 0 ? tenders : recommendations).slice(0, 6).map((t) => (
+          {(recommendations.length > 0 || tenders.length > 0) ? (
+            (recommendations.length > 0 ? recommendations : tenders).slice(0, 6).map((t) => (
               // ... existing map logic ...
               <div 
                 key={t.code}