lower query and name/add fuzzy brand

app.py

@@ -28,7 +28,7 @@ table = api.table(BASE_ID, TABLE_NAME)
 # Preload Models
 model = SentenceTransformer("BAAI/bge-m3")
 collection_name = "product_bge-m3"
-threshold = 0.45
+threshold = 0.5
 
 # Utils
 def is_non_thai(text):
@@ -71,20 +71,28 @@ def search_product(query):
 
       scored = []
       for r in result:
-          name = r.payload.get("name", "")
+          name = str(r.payload.get("name", "")).lower()
+          brand = str(r.payload.get("brand", "")).lower()
+          query_lower = corrected_query.lower()
 
           # ถ้า query สั้นเกินไป ให้ fuzzy_score = 0 เพื่อกันเพี้ยน
           if len(corrected_query) >= 3 and name:
-            fuzzy_score = fuzz.partial_ratio(corrected_query, name) / 100.0
+            fuzzy_name_score = fuzz.partial_ratio(query_lower, name) / 100.0
+            fuzzy_brand_score = fuzz.partial_ratio(query_lower, brand) / 100.0
           else:
-            fuzzy_score = 0.0
+            fuzzy_name_score = 0.0
+            fuzzy_brand_score = fuzz.partial_ratio(query_lower, brand) / 100.0
+
           # รวม hybrid score
-          if fuzzy_score < 0.5:
+          if fuzzy_name_score < 0.5:
             hybrid_score = r.score
           else:
-            hybrid_score = 0.7 * r.score + 0.3 * fuzzy_score
+            hybrid_score = 0.7 * r.score + 0.3 * fuzzy_name_score
+          if fuzzy_brand_score >= 0.8:
+            hybrid_score = hybrid_score*1.2
           r.payload["score"] = hybrid_score  # เก็บลง payload ใช้เทียบ treshold ตอนเเสดงผล
-          r.payload["fuzzy_score"] = fuzzy_score # เก็บไว้เผื่อ debug
+          r.payload["fuzzy_name_score"] = fuzzy_name_score # เก็บไว้เผื่อ debug
+          r.payload["fuzzy_brand_score"] = fuzzy_brand_score # เก็บไว้เผื่อ debug
           r.payload['semantic_score'] = r.score # เก็บไว้เผื่อ debug
           scored.append((r, hybrid_score))