remove fuzzy

app.py

@@ -6,13 +6,9 @@ from sentence_transformers import SentenceTransformer
 from qdrant_client import QdrantClient
 from qdrant_client.models import Filter, FieldCondition, MatchValue
 import os
-from rapidfuzz import process, fuzz
 from pythainlp.tokenize import word_tokenize
 from pyairtable import Table
 from pyairtable import Api
-import pickle
-import re
-import unicodedata
 
 
 qdrant_client = QdrantClient(
@@ -52,41 +48,6 @@ model_config = {
 # Global memory to hold feedback state
 latest_query_result = {"query": "", "result": "", "model": "", "raw_query": "", "time": ""}
 
-with open("keyword_whitelist.pkl", "rb") as f:
-    keyword_whitelist = pickle.load(f)
-
-def smart_tokenize(query: str) -> list:
-    tokens = word_tokenize(query, engine="newmm")
-    if len("".join(tokens)) < len(query) * 0.7:  # ตัดคำขาดเกินไป
-        return query.strip().split()
-    return tokens
-
-def normalize_and_clean_thai(text: str) -> str:
-    text = unicodedata.normalize("NFC", text)
-    text = text.replace("เแ", "แ").replace("เเ", "แ")
-    return text
-
-def correct_query_smart(query: str, whitelist=None, threshold=70) -> str:
-    query_norm = normalize_and_clean_thai(query)
-    tokens = query_norm.strip().split()
-
-    # ถ้า token เดียว → fuzzy ตรงไปที่คำเต็มเลย
-    if len(tokens) == 1:
-        match, score, _ = process.extractOne(tokens[0].lower(), whitelist, scorer=fuzz.token_sort_ratio)
-        return match if score >= threshold else query_norm
-
-    # token หลายคำ → ลองแก้ทีละคำ
-    corrected = []
-    for word in tokens:
-        word_lower = word.lower()
-        if word_lower in whitelist:
-            corrected.append(word)
-        else:
-            match, score, _ = process.extractOne(word_lower, whitelist, scorer=fuzz.token_sort_ratio)
-            corrected.append(match if score >= threshold else word)
-
-    return " ".join(corrected)
-
 # 🌟 Main search function
 def search_product(query, model_name):
     start_time = time.time()
@@ -94,7 +55,7 @@ def search_product(query, model_name):
         return "<p>❌ ไม่พบโมเดล</p>"
 
     latest_query_result["raw_query"] = query
-    corrected_query = correct_query_smart(query,keyword_whitelist)
+    corrected_query = query
 
     query_embed = model_config[model_name]["func"](corrected_query)
     collection_name = model_config[model_name]["collection"]