diff --git a/pythainlp/augment/lm/phayathaibert.py b/pythainlp/augment/lm/phayathaibert.py
index 47b43c219..8ba41a241 100644
--- a/pythainlp/augment/lm/phayathaibert.py
+++ b/pythainlp/augment/lm/phayathaibert.py
@@ -13,21 +13,31 @@
 
 
 class ThaiTextAugmenter:
-    def __init__(self,) -> None:
-        from transformers import (AutoTokenizer,
-                                  AutoModelForMaskedLM,
-                                  pipeline,)
+    def __init__(self) -> None:
+        from transformers import (
+            AutoTokenizer,
+            AutoModelForMaskedLM,
+            pipeline,
+        )
+
         self.tokenizer = AutoTokenizer.from_pretrained(_MODEL_NAME)
-        self.model_for_masked_lm = AutoModelForMaskedLM.from_pretrained(_MODEL_NAME)
-        self.model = pipeline("fill-mask", tokenizer=self.tokenizer, model=self.model_for_masked_lm)
+        self.model_for_masked_lm = AutoModelForMaskedLM.from_pretrained(
+            _MODEL_NAME
+        )
+        self.model = pipeline(
+            "fill-mask",
+            tokenizer=self.tokenizer,
+            model=self.model_for_masked_lm,
+        )
         self.processor = ThaiTextProcessor()
 
-    def generate(self,
-                 sample_text: str,
-                 word_rank: int,
-                 max_length: int = 3,
-                 sample: bool = False
-                 ) -> str:
+    def generate(
+        self,
+        sample_text: str,
+        word_rank: int,
+        max_length: int = 3,
+        sample: bool = False,
+    ) -> str:
         sample_txt = sample_text
         final_text = ""
 
@@ -45,11 +55,9 @@ def generate(self,
 
         return gen_txt
 
-    def augment(self,
-                text: str,
-                num_augs: int = 3,
-                sample: bool = False
-                ) -> List[str]:
+    def augment(
+        self, text: str, num_augs: int = 3, sample: bool = False
+    ) -> List[str]:
         """
         Text augmentation from PhayaThaiBERT
 
@@ -84,11 +92,13 @@ def augment(self,
         if num_augs <= MAX_NUM_AUGS:
             for rank in range(num_augs):
                 gen_text = self.generate(text, rank, sample=sample)
-                processed_text = re.sub("<_>", " ", self.processor.preprocess(gen_text))
+                processed_text = re.sub(
+                    "<_>", " ", self.processor.preprocess(gen_text)
+                )
                 augment_list.append(processed_text)
+        else:
+            raise ValueError(
+                f"augmentation of more than {num_augs} is exceeded the default limit: {MAX_NUM_AUGS}"
+            )
 
-            return augment_list
-
-        raise ValueError(
-            f"augmentation of more than {num_augs} is exceeded the default limit: {MAX_NUM_AUGS}"
-        )
+        return augment_list
diff --git a/pythainlp/augment/lm/wangchanberta.py b/pythainlp/augment/lm/wangchanberta.py
index 595378186..1299654da 100644
--- a/pythainlp/augment/lm/wangchanberta.py
+++ b/pythainlp/augment/lm/wangchanberta.py
@@ -1,7 +1,9 @@
 # -*- coding: utf-8 -*-
 # SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
 # SPDX-License-Identifier: Apache-2.0
+
 from typing import List
+
 from transformers import (
     CamembertTokenizer,
     pipeline,
@@ -51,9 +53,9 @@ def generate(self, sentence: str, num_replace_tokens: int = 3):
 
     def augment(self, sentence: str, num_replace_tokens: int = 3) -> List[str]:
         """
-        Text Augment from wangchanberta
+        Text augmentation from WangchanBERTa
 
-        :param str sentence: thai sentence
+        :param str sentence: Thai sentence
         :param int num_replace_tokens: number replace tokens
 
         :return: list of text augment
@@ -64,7 +66,7 @@ def augment(self, sentence: str, num_replace_tokens: int = 3) -> List[str]:
 
             from pythainlp.augment.lm import Thai2transformersAug
 
-            aug=Thai2transformersAug()
+            aug = Thai2transformersAug()
 
             aug.augment("ช้างมีทั้งหมด 50 ตัว บน")
             # output: ['ช้างมีทั้งหมด 50 ตัว บนโลกใบนี้',
diff --git a/pythainlp/augment/wordnet.py b/pythainlp/augment/wordnet.py
index 99b0d2c3a..0665bd6c7 100644
--- a/pythainlp/augment/wordnet.py
+++ b/pythainlp/augment/wordnet.py
@@ -12,6 +12,7 @@
 from collections import OrderedDict
 import itertools
 from typing import List
+
 from nltk.corpus import wordnet as wn
 from pythainlp.corpus import wordnet
 from pythainlp.tokenize import word_tokenize
diff --git a/pythainlp/khavee/__init__.py b/pythainlp/khavee/__init__.py
index 4efbf2f62..9afefe8c3 100644
--- a/pythainlp/khavee/__init__.py
+++ b/pythainlp/khavee/__init__.py
@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 # SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
 # SPDX-License-Identifier: Apache-2.0
+
 __all__ = ["KhaveeVerifier"]
 
 from pythainlp.khavee.core import KhaveeVerifier
diff --git a/pythainlp/khavee/core.py b/pythainlp/khavee/core.py
index 468d26a82..0bedff0de 100644
--- a/pythainlp/khavee/core.py
+++ b/pythainlp/khavee/core.py
@@ -1,10 +1,14 @@
 # -*- coding: utf-8 -*-
 # SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
 # SPDX-License-Identifier: Apache-2.0
+# ruff: noqa: C901
+
 from typing import List, Union
+
 from pythainlp.tokenize import subword_tokenize
-from pythainlp.util import sound_syllable
-from pythainlp.util import remove_tonemark
+from pythainlp.util import remove_tonemark, sound_syllable
+
+
 class KhaveeVerifier:
     def __init__(self):
         """
@@ -26,166 +30,179 @@ def check_sara(self, word: str) -> str:
 
             kv = KhaveeVerifier()
 
-            print(kv.check_sara('เริง'))
+            print(kv.check_sara("เริง"))
             # output: 'เออ'
         """
         sara = []
         countoa = 0
+
         # In case of การันย์
-        if '์' in word[-1]:
+        if "์" in word[-1]:
             word = word[:-2]
+
         # In case of สระเดี่ยว
         for i in word:
-            if i in ('ะ', 'ั'):
-                sara.append('อะ')
-            elif i == 'ิ':
-                sara.append('อิ')
-            elif i == 'ุ':
-                sara.append('อุ')
-            elif i == 'ึ':
-                sara.append('อึ')
-            elif i == 'ี':
-                sara.append('อี')
-            elif i == 'ู':
-                sara.append('อู')
-            elif i == 'ื':
-                sara.append('อือ')
-            elif i == 'เ':
-                sara.append('เอ')
-            elif i == 'แ':
-                sara.append('แอ')
-            elif i == 'า':
-                sara.append('อา')
-            elif i == 'โ':
-                sara.append('โอ')
-            elif i == 'ำ':
-                sara.append('อำ')
-            elif i == 'อ':
+            if i in ("ะ", "ั"):
+                sara.append("อะ")
+            elif i == "ิ":
+                sara.append("อิ")
+            elif i == "ุ":
+                sara.append("อุ")
+            elif i == "ึ":
+                sara.append("อึ")
+            elif i == "ี":
+                sara.append("อี")
+            elif i == "ู":
+                sara.append("อู")
+            elif i == "ื":
+                sara.append("อือ")
+            elif i == "เ":
+                sara.append("เอ")
+            elif i == "แ":
+                sara.append("แอ")
+            elif i == "า":
+                sara.append("อา")
+            elif i == "โ":
+                sara.append("โอ")
+            elif i == "ำ":
+                sara.append("อำ")
+            elif i == "อ":
                 countoa += 1
-                sara.append('ออ')
-            elif i == 'ั' and 'ว' in word:
-                sara.append('อัว')
-            elif i in ('ไ', 'ใ'):
-                sara.append('ไอ')
-            elif i == '็':
-                sara.append('ออ')
-            elif 'รร' in word:
-                if self.check_marttra(word) == 'กม':
-                    sara.append('อำ')
+                sara.append("ออ")
+            elif i == "ั" and "ว" in word:
+                sara.append("อัว")
+            elif i in ("ไ", "ใ"):
+                sara.append("ไอ")
+            elif i == "็":
+                sara.append("ออ")
+            elif "รร" in word:
+                if self.check_marttra(word) == "กม":
+                    sara.append("อำ")
                 else:
-                    sara.append('อะ')
+                    sara.append("อะ")
+
         # In case of ออ
-        if countoa == 1 and 'อ' in word[-1] and 'เ' not in word:
-            sara.remove('ออ')
+        if countoa == 1 and "อ" in word[-1] and "เ" not in word:
+            sara.remove("ออ")
+
         # In case of เอ เอ
         countA = 0
         for i in sara:
-            if i == 'เอ':
+            if i == "เอ":
                 countA = countA + 1
             if countA > 1:
-                sara.remove('เอ')
-                sara.remove('เอ')
-                sara.append('แ')
+                sara.remove("เอ")
+                sara.remove("เอ")
+                sara.append("แ")
+
         # In case of สระประสม
-        if 'เอ' in sara and 'อะ' in sara:
-            sara.remove('เอ')
-            sara.remove('อะ')
-            sara.append('เอะ')
-        elif 'แอ' in sara and 'อะ' in sara:
-            sara.remove('แอ')
-            sara.remove('อะ')
-            sara.append('แอะ')
-        if 'เอะ' in sara and 'ออ' in sara:
-            sara.remove('เอะ')
-            sara.remove('ออ')
-            sara.append('เออะ')
-        elif 'เอ' in sara and 'อิ' in sara:
-            sara.remove('เอ')
-            sara.remove('อิ')
-            sara.append('เออ')
-        elif 'เอ' in sara and 'ออ' in sara and 'อ' in word[-1]:
-            sara.remove('เอ')
-            sara.remove('ออ')
-            sara.append('เออ')
-        elif 'โอ' in sara and 'อะ' in sara:
-            sara.remove('โอ')
-            sara.remove('อะ')
-            sara.append('โอะ')
-        elif 'เอ' in sara and 'อี' in sara:
-            sara.remove('เอ')
-            sara.remove('อี')
-            sara.append('เอีย')
-        elif 'เอ' in sara and 'อือ' in sara:
-            sara.remove('เอ')
-            sara.remove('อือ')
-            sara.append('อัว')
-        elif 'เอ' in sara and 'อา' in sara:
-            sara.remove('เอ')
-            sara.remove('อา')
-            sara.append('เอา')
-        elif 'เ' in word and 'า' in word and 'ะ' in word:
+        if "เอ" in sara and "อะ" in sara:
+            sara.remove("เอ")
+            sara.remove("อะ")
+            sara.append("เอะ")
+        elif "แอ" in sara and "อะ" in sara:
+            sara.remove("แอ")
+            sara.remove("อะ")
+            sara.append("แอะ")
+
+        if "เอะ" in sara and "ออ" in sara:
+            sara.remove("เอะ")
+            sara.remove("ออ")
+            sara.append("เออะ")
+        elif "เอ" in sara and "อิ" in sara:
+            sara.remove("เอ")
+            sara.remove("อิ")
+            sara.append("เออ")
+        elif "เอ" in sara and "ออ" in sara and "อ" in word[-1]:
+            sara.remove("เอ")
+            sara.remove("ออ")
+            sara.append("เออ")
+        elif "โอ" in sara and "อะ" in sara:
+            sara.remove("โอ")
+            sara.remove("อะ")
+            sara.append("โอะ")
+        elif "เอ" in sara and "อี" in sara:
+            sara.remove("เอ")
+            sara.remove("อี")
+            sara.append("เอีย")
+        elif "เอ" in sara and "อือ" in sara:
+            sara.remove("เอ")
+            sara.remove("อือ")
+            sara.append("อัว")
+        elif "เอ" in sara and "อา" in sara:
+            sara.remove("เอ")
+            sara.remove("อา")
+            sara.append("เอา")
+        elif "เ" in word and "า" in word and "ะ" in word:
             sara = []
-            sara.append('เอาะ')
-        if 'อือ' in sara and 'เออ' in sara:
-            sara.remove('เออ')
-            sara.remove('อือ')
-            sara.append('เอือ')
-        elif 'ออ' in sara and len(sara) > 1:
-            sara.remove('ออ')
-        elif 'ว' in word and len(sara) == 0:
-            sara.append('อัว')
-        if 'ั' in word and self.check_marttra(word) == 'กา':
+            sara.append("เอาะ")
+
+        if "อือ" in sara and "เออ" in sara:
+            sara.remove("เออ")
+            sara.remove("อือ")
+            sara.append("เอือ")
+        elif "ออ" in sara and len(sara) > 1:
+            sara.remove("ออ")
+        elif "ว" in word and len(sara) == 0:
+            sara.append("อัว")
+
+        if "ั" in word and self.check_marttra(word) == "กา":
             sara = []
-            sara.append('ไอ')
+            sara.append("ไอ")
+
         # In case of อ
-        if word == 'เออะ':
+        if word == "เออะ":
             sara = []
-            sara.append('เออะ')
-        elif word == 'เออ':
+            sara.append("เออะ")
+        elif word == "เออ":
             sara = []
-            sara.append('เออ')
-        elif word == 'เอ':
+            sara.append("เออ")
+        elif word == "เอ":
             sara = []
-            sara.append('เอ')
-        elif word == 'เอะ':
+            sara.append("เอ")
+        elif word == "เอะ":
             sara = []
-            sara.append('เอะ')
-        elif word == 'เอา':
+            sara.append("เอะ")
+        elif word == "เอา":
             sara = []
-            sara.append('เอา')
-        elif word == 'เอาะ':
+            sara.append("เอา")
+        elif word == "เอาะ":
             sara = []
-            sara.append('เอาะ')
-        if 'ฤา' in word or 'ฦา' in word:
+            sara.append("เอาะ")
+
+        if "ฤา" in word or "ฦา" in word:
             sara = []
-            sara.append('อือ')
-        elif 'ฤ' in word or 'ฦ' in word:
+            sara.append("อือ")
+        elif "ฤ" in word or "ฦ" in word:
             sara = []
-            sara.append('อึ')
+            sara.append("อึ")
+
         # In case of กน
         if not sara and len(word) == 2:
-            if word[-1] != 'ร':
-                sara.append('โอะ')
+            if word[-1] != "ร":
+                sara.append("โอะ")
             else:
-                sara.append('ออ')
+                sara.append("ออ")
         elif not sara and len(word) == 3:
-            sara.append('ออ')
+            sara.append("ออ")
 
         # In case of บ่
-        if 'บ่' == word:
+        if word == "บ่":
             sara = []
-            sara.append('ออ')
-        if 'ํ' in word:
+            sara.append("ออ")
+
+        if "ํ" in word:
             sara = []
-            sara.append('อำ')
-        if 'เ' in word and 'ื' in word and 'อ' in word:
+            sara.append("อำ")
+
+        if "เ" in word and "ื" in word and "อ" in word:
             sara = []
-            sara.append('เอือ')
+            sara.append("เอือ")
+
         if not sara:
-            return 'Can\'t find Sara in this word'
-        else:
-            return sara[0]
+            return "Can't find Sara in this word"
 
+        return sara[0]
 
     def check_marttra(self, word: str) -> str:
         """
@@ -205,44 +222,64 @@ def check_marttra(self, word: str) -> str:
             print(kv.check_marttra('สาว'))
             # output: 'เกอว'
         """
-        if word[-1] == 'ร' and word[-2] in ['ต', 'ท']:
+        if word[-1] == "ร" and word[-2] in ["ต", "ท"]:
             word = word[:-1]
         word = self.handle_karun_sound_silence(word)
         word = remove_tonemark(word)
-        if 'ำ' in word or ('ํ' in word and 'า' in word) or 'ไ' in word or 'ใ' in word:
-            return 'กา'
+        if (
+            "ำ" in word
+            or ("ํ" in word and "า" in word)
+            or "ไ" in word
+            or "ใ" in word
+        ):
+            return "กา"
         elif (
-            word[-1] in ['า', 'ะ', 'ิ', 'ี', 'ุ', 'ู', 'อ'] or
-            ('ี' in word and 'ย' in word[-1]) or
-            ('ื' in word and 'อ' in word[-1])
+            word[-1] in ["า", "ะ", "ิ", "ี", "ุ", "ู", "อ"]
+            or ("ี" in word and "ย" in word[-1])
+            or ("ื" in word and "อ" in word[-1])
         ):
-            return 'กา'
-        elif word[-1] in ['ง']:
-            return 'กง'
-        elif word[-1] in ['ม']:
-            return 'กม'
-        elif word[-1] in ['ย']:
-            if 'ั' in word:
-                return 'กา'
+            return "กา"
+        elif word[-1] in ["ง"]:
+            return "กง"
+        elif word[-1] in ["ม"]:
+            return "กม"
+        elif word[-1] in ["ย"]:
+            if "ั" in word:
+                return "กา"
             else:
-                return 'เกย'
-        elif word[-1] in ['ว']:
-            return 'เกอว'
-        elif word[-1] in ['ก', 'ข', 'ค', 'ฆ']:
-            return 'กก'
+                return "เกย"
+        elif word[-1] in ["ว"]:
+            return "เกอว"
+        elif word[-1] in ["ก", "ข", "ค", "ฆ"]:
+            return "กก"
         elif word[-1] in [
-            'จ', 'ช', 'ซ', 'ฎ', 'ฏ', 'ฐ', 'ฑ', 'ฒ', 'ด', 'ต', 'ถ', 'ท', 'ธ', 'ศ', 'ษ', 'ส'
+            "จ",
+            "ช",
+            "ซ",
+            "ฎ",
+            "ฏ",
+            "ฐ",
+            "ฑ",
+            "ฒ",
+            "ด",
+            "ต",
+            "ถ",
+            "ท",
+            "ธ",
+            "ศ",
+            "ษ",
+            "ส",
         ]:
-            return 'กด'
-        elif word[-1] in ['ญ', ', ณ', 'น', 'ร', 'ล', 'ฬ']:
-            return 'กน'
-        elif word[-1] in ['บ', 'ป', 'พ', 'ฟ', 'ภ']:
-            return 'กบ'
+            return "กด"
+        elif word[-1] in ["ญ", ", ณ", "น", "ร", "ล", "ฬ"]:
+            return "กน"
+        elif word[-1] in ["บ", "ป", "พ", "ฟ", "ภ"]:
+            return "กบ"
         else:
-            if '็' in word:
-                return 'กา'
+            if "็" in word:
+                return "กา"
             else:
-                return 'Cant find Marttra in this word'
+                return "Cant find Marttra in this word"
 
     def is_sumpus(self, word1: str, word2: str) -> bool:
         """
@@ -270,39 +307,46 @@ def is_sumpus(self, word1: str, word2: str) -> bool:
         marttra2 = self.check_marttra(word2)
         sara1 = self.check_sara(word1)
         sara2 = self.check_sara(word2)
-        if sara1 == 'อะ' and marttra1 == 'เกย':
-            sara1 = 'ไอ'
-            marttra1 = 'กา'
-        elif sara2 == 'อะ' and marttra2 == 'เกย':
-            sara2 = 'ไอ'
-            marttra2 = 'กา'
-        if sara1 == 'อำ' and marttra1 == 'กม':
-            sara1 = 'อำ'
-            marttra1 = 'กา'
-        elif sara2 == 'อำ' and marttra2 == 'กม':
-            sara2 = 'อำ'
-            marttra2 = 'กา'
+        if sara1 == "อะ" and marttra1 == "เกย":
+            sara1 = "ไอ"
+            marttra1 = "กา"
+        elif sara2 == "อะ" and marttra2 == "เกย":
+            sara2 = "ไอ"
+            marttra2 = "กา"
+        if sara1 == "อำ" and marttra1 == "กม":
+            sara1 = "อำ"
+            marttra1 = "กา"
+        elif sara2 == "อำ" and marttra2 == "กม":
+            sara2 = "อำ"
+            marttra2 = "กา"
         return bool(marttra1 == marttra2 and sara1 == sara2)
 
     def check_karu_lahu(self, text):
         if (
-            (
-                self.check_marttra(text) != 'กา' or
-                (
-                    self.check_marttra(text) == 'กา' and
-                    self.check_sara(text) in [
-                        'อา', 'อี', 'อือ', 'อู', 'เอ',
-                        'แอ', 'โอ', 'ออ', 'เออ', 'เอีย',
-                        'เอือ', 'อัว'
-                    ]
-                ) or
-                self.check_sara(text) in ['อำ', 'ไอ', 'เอา']
-            ) and
-            text not in ['บ่', 'ณ', 'ธ', 'ก็']
-        ):
-            return 'karu'
+            self.check_marttra(text) != "กา"
+            or (
+                self.check_marttra(text) == "กา"
+                and self.check_sara(text)
+                in [
+                    "อา",
+                    "อี",
+                    "อือ",
+                    "อู",
+                    "เอ",
+                    "แอ",
+                    "โอ",
+                    "ออ",
+                    "เออ",
+                    "เอีย",
+                    "เอือ",
+                    "อัว",
+                ]
+            )
+            or self.check_sara(text) in ["อำ", "ไอ", "เอา"]
+        ) and text not in ["บ่", "ณ", "ธ", "ก็"]:
+            return "karu"
         else:
-            return 'lahu'
+            return "lahu"
 
     def check_klon(self, text: str, k_type: int = 8) -> Union[List[str], str]:
         """
@@ -346,19 +390,24 @@ def check_klon(self, text: str, k_type: int = 8) -> Union[List[str], str]:
                 list_sumpus_sent3 = []
                 list_sumpus_sent4 = []
                 for i, sent in enumerate(text.split()):
-                    sub_sent = subword_tokenize(sent, engine='dict')
+                    sub_sent = subword_tokenize(sent, engine="dict")
                     if len(sub_sent) > 10:
                         error.append(
-                            'In sentence ' +
-                            str(i + 2) +
-                            ', there are more than 10 words. ' +
-                            str(sub_sent)
+                            "In sentence "
+                            + str(i + 2)
+                            + ", there are more than 10 words. "
+                            + str(sub_sent)
                         )
                     if (i + 1) % 4 == 1:
                         list_sumpus_sent1.append(sub_sent[-1])
                     elif (i + 1) % 4 == 2:
                         list_sumpus_sent2h.append(
-                            [sub_sent[1], sub_sent[2], sub_sent[3], sub_sent[4]]
+                            [
+                                sub_sent[1],
+                                sub_sent[2],
+                                sub_sent[3],
+                                sub_sent[4],
+                            ]
                         )
                         list_sumpus_sent2l.append(sub_sent[-1])
                     elif (i + 1) % 4 == 3:
@@ -366,49 +415,78 @@ def check_klon(self, text: str, k_type: int = 8) -> Union[List[str], str]:
                     elif (i + 1) % 4 == 0:
                         list_sumpus_sent4.append(sub_sent[-1])
                 if (
-                    len(list_sumpus_sent1) != len(list_sumpus_sent2h) or
-                    len(list_sumpus_sent2h) != len(list_sumpus_sent2l) or
-                    len(list_sumpus_sent2l) != len(list_sumpus_sent3) or
-                    len(list_sumpus_sent3) != len(list_sumpus_sent4) or
-                    len(list_sumpus_sent4) != len(list_sumpus_sent1)
+                    len(list_sumpus_sent1) != len(list_sumpus_sent2h)
+                    or len(list_sumpus_sent2h) != len(list_sumpus_sent2l)
+                    or len(list_sumpus_sent2l) != len(list_sumpus_sent3)
+                    or len(list_sumpus_sent3) != len(list_sumpus_sent4)
+                    or len(list_sumpus_sent4) != len(list_sumpus_sent1)
                 ):
-                    return 'The poem does not have 4 complete sentences.'
+                    return "The poem does not have 4 complete sentences."
                 else:
                     for i in range(len(list_sumpus_sent1)):
                         countwrong = 0
                         for j in list_sumpus_sent2h[i]:
-                            if self.is_sumpus(list_sumpus_sent1[i], j) is False:
+                            if (
+                                self.is_sumpus(list_sumpus_sent1[i], j)
+                                is False
+                            ):
                                 countwrong += 1
                         if countwrong > 3:
                             error.append(
-                                'Can\'t find rhyme between paragraphs ' +
-                                str((list_sumpus_sent1[i], list_sumpus_sent2h[i])) +
-                                ' in paragraph ' +
-                                str(i + 1)
+                                "Can't find rhyme between paragraphs "
+                                + str(
+                                    (
+                                        list_sumpus_sent1[i],
+                                        list_sumpus_sent2h[i],
+                                    )
+                                )
+                                + " in paragraph "
+                                + str(i + 1)
+                            )
+                        if (
+                            self.is_sumpus(
+                                list_sumpus_sent2l[i], list_sumpus_sent3[i]
                             )
-                        if self.is_sumpus(list_sumpus_sent2l[i], list_sumpus_sent3[i]) is False:
+                            is False
+                        ):
                             error.append(
-                                'Can\'t find rhyme between paragraphs ' +
-                                str((list_sumpus_sent2l[i], list_sumpus_sent3[i])) +
-                                ' in paragraph ' +
-                                str(i + 1)
+                                "Can't find rhyme between paragraphs "
+                                + str(
+                                    (
+                                        list_sumpus_sent2l[i],
+                                        list_sumpus_sent3[i],
+                                    )
+                                )
+                                + " in paragraph "
+                                + str(i + 1)
                             )
                         if i > 0:
-                            if self.is_sumpus(
-                                list_sumpus_sent2l[i], list_sumpus_sent4[i - 1]
-                            ) is False:
+                            if (
+                                self.is_sumpus(
+                                    list_sumpus_sent2l[i],
+                                    list_sumpus_sent4[i - 1],
+                                )
+                                is False
+                            ):
                                 error.append(
-                                    'Can\'t find rhyme between paragraphs ' +
-                                    str((list_sumpus_sent2l[i], list_sumpus_sent4[i - 1])) +
-                                    ' in paragraph ' +
-                                    str(i + 1)
+                                    "Can't find rhyme between paragraphs "
+                                    + str(
+                                        (
+                                            list_sumpus_sent2l[i],
+                                            list_sumpus_sent4[i - 1],
+                                        )
+                                    )
+                                    + " in paragraph "
+                                    + str(i + 1)
                                 )
                     if not error:
-                        return 'The poem is correct according to the principle.'
+                        return (
+                            "The poem is correct according to the principle."
+                        )
                     else:
                         return error
             except:
-                return 'Something went wrong. Make sure you enter it in the correct form of klon 8.'
+                return "Something went wrong. Make sure you enter it in the correct form of klon 8."
         elif k_type == 4:
             try:
                 error = []
@@ -418,13 +496,13 @@ def check_klon(self, text: str, k_type: int = 8) -> Union[List[str], str]:
                 list_sumpus_sent3 = []
                 list_sumpus_sent4 = []
                 for i, sent in enumerate(text.split()):
-                    sub_sent = subword_tokenize(sent, engine='dict')
+                    sub_sent = subword_tokenize(sent, engine="dict")
                     if len(sub_sent) > 5:
                         error.append(
-                            'In sentence ' +
-                            str(i + 2) +
-                            ', there are more than 4 words. ' +
-                            str(sub_sent)
+                            "In sentence "
+                            + str(i + 2)
+                            + ", there are more than 4 words. "
+                            + str(sub_sent)
                         )
                     if (i + 1) % 4 == 1:
                         list_sumpus_sent1.append(sub_sent[-1])
@@ -436,57 +514,84 @@ def check_klon(self, text: str, k_type: int = 8) -> Union[List[str], str]:
                     elif (i + 1) % 4 == 0:
                         list_sumpus_sent4.append(sub_sent[-1])
                 if (
-                    len(list_sumpus_sent1) != len(list_sumpus_sent2h) or
-                    len(list_sumpus_sent2h) != len(list_sumpus_sent2l) or
-                    len(list_sumpus_sent2l) != len(list_sumpus_sent3) or
-                    len(list_sumpus_sent3) != len(list_sumpus_sent4) or
-                    len(list_sumpus_sent4) != len(list_sumpus_sent1)
+                    len(list_sumpus_sent1) != len(list_sumpus_sent2h)
+                    or len(list_sumpus_sent2h) != len(list_sumpus_sent2l)
+                    or len(list_sumpus_sent2l) != len(list_sumpus_sent3)
+                    or len(list_sumpus_sent3) != len(list_sumpus_sent4)
+                    or len(list_sumpus_sent4) != len(list_sumpus_sent1)
                 ):
-                    return 'The poem does not have 4 complete sentences.'
+                    return "The poem does not have 4 complete sentences."
                 else:
                     for i in range(len(list_sumpus_sent1)):
                         countwrong = 0
                         for j in list_sumpus_sent2h[i]:
-                            if self.is_sumpus(list_sumpus_sent1[i], j) is False:
+                            if (
+                                self.is_sumpus(list_sumpus_sent1[i], j)
+                                is False
+                            ):
                                 countwrong += 1
                         if countwrong > 1:
                             error.append(
-                                'Can\'t find rhyme between paragraphs ' +
-                                str((list_sumpus_sent1[i], list_sumpus_sent2h[i])) +
-                                ' in paragraph ' +
-                                str(i + 1)
+                                "Can't find rhyme between paragraphs "
+                                + str(
+                                    (
+                                        list_sumpus_sent1[i],
+                                        list_sumpus_sent2h[i],
+                                    )
+                                )
+                                + " in paragraph "
+                                + str(i + 1)
+                            )
+                        if (
+                            self.is_sumpus(
+                                list_sumpus_sent2l[i], list_sumpus_sent3[i]
                             )
-                        if self.is_sumpus(list_sumpus_sent2l[i], list_sumpus_sent3[i]) is False:
+                            is False
+                        ):
                             error.append(
-                                'Can\'t find rhyme between paragraphs ' +
-                                str((list_sumpus_sent2l[i], list_sumpus_sent3[i])) +
-                                ' in paragraph ' +
-                                str(i + 1)
+                                "Can't find rhyme between paragraphs "
+                                + str(
+                                    (
+                                        list_sumpus_sent2l[i],
+                                        list_sumpus_sent3[i],
+                                    )
+                                )
+                                + " in paragraph "
+                                + str(i + 1)
                             )
                         if i > 0:
-                            if self.is_sumpus(
-                                list_sumpus_sent2l[i], list_sumpus_sent4[i - 1]
-                            ) is False:
+                            if (
+                                self.is_sumpus(
+                                    list_sumpus_sent2l[i],
+                                    list_sumpus_sent4[i - 1],
+                                )
+                                is False
+                            ):
                                 error.append(
-                                    'Can\'t find rhyme between paragraphs ' +
-                                    str((list_sumpus_sent2l[i], list_sumpus_sent4[i - 1])) +
-                                    ' in paragraph ' +
-                                    str(i + 1)
+                                    "Can't find rhyme between paragraphs "
+                                    + str(
+                                        (
+                                            list_sumpus_sent2l[i],
+                                            list_sumpus_sent4[i - 1],
+                                        )
+                                    )
+                                    + " in paragraph "
+                                    + str(i + 1)
                                 )
                     if not error:
-                        return 'The poem is correct according to the principle.'
+                        return (
+                            "The poem is correct according to the principle."
+                        )
                     else:
                         return error
             except:
-                return 'Something went wrong. Make sure you enter it in the correct form.'
+                return "Something went wrong. Make sure you enter it in the correct form."
 
         else:
-            return 'Something went wrong. Make sure you enter it in the correct form.'
+            return "Something went wrong. Make sure you enter it in the correct form."
 
     def check_aek_too(
-        self,
-        text: Union[List[str], str],
-        dead_syllable_as_aek: bool = False
+        self, text: Union[List[str], str], dead_syllable_as_aek: bool = False
     ) -> Union[List[bool], List[str], bool, str]:
         """
         Checker of Thai tonal words
@@ -515,15 +620,15 @@ def check_aek_too(
             return [self.check_aek_too(t, dead_syllable_as_aek) for t in text]
 
         if not isinstance(text, str):
-            raise TypeError('text must be str or iterable list[str]')
+            raise TypeError("text must be str or iterable list[str]")
 
         word_characters = [*text]
-        if '่' in word_characters and not '้' in word_characters:
-            return 'aek'
-        elif '้' in word_characters and not '่' in word_characters:
-            return 'too'
-        if dead_syllable_as_aek and sound_syllable(text) == 'dead':
-            return 'aek'
+        if "่" in word_characters and not "้" in word_characters:
+            return "aek"
+        elif "้" in word_characters and not "่" in word_characters:
+            return "too"
+        if dead_syllable_as_aek and sound_syllable(text) == "dead":
+            return "aek"
         else:
             return False
 
@@ -536,12 +641,12 @@ def handle_karun_sound_silence(self, word: str) -> str:
         :return: Thai word with silent words stripped
         :rtype: str
         """
-        sound_silenced = word.endswith('์')
+        sound_silenced = word.endswith("์")
         if not sound_silenced:
             return word
         thai_consonants = "กขฃคฅฆงจฉชซฌญฎฏฐฑฒณดตถทธนบปผฝพฟภมยรลวศษสหฬอฮ"
-        locate_silenced = word.rfind('์') - 1
-        can_silence_two = word[locate_silenced-2] in thai_consonants
+        locate_silenced = word.rfind("์") - 1
+        can_silence_two = word[locate_silenced - 2] in thai_consonants
         cut_off = 2 if can_silence_two else 1
-        word = word[:locate_silenced + 1 - cut_off]
+        word = word[: locate_silenced + 1 - cut_off]
         return word
diff --git a/pythainlp/khavee/example.py b/pythainlp/khavee/example.py
index 6fd1a7a3e..e1fd1e9b4 100644
--- a/pythainlp/khavee/example.py
+++ b/pythainlp/khavee/example.py
@@ -1,34 +1,40 @@
 # -*- coding: utf-8 -*-
+# SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
+# SPDX-License-Identifier: Apache-2.0
+
 import core
+
 kv = core.KhaveeVerifier()
 
 
 # การเช็คสระ
-print('เออ', kv.check_sara('เมอ'))
+print("เออ", kv.check_sara("เมอ"))
 # 'เออ'
 
 # การเช็คมาตราตัวสะกด
-print('เทอว', kv.check_marttra('เทอว'))
+print("เทอว", kv.check_marttra("เทอว"))
 # 'เกอว'
 
 # การตรวจสอบคำสำผัสที่ถูกต้อง
-print('สรร อัน', kv.is_sumpus('สรร', 'อัน'))
+print("สรร อัน", kv.is_sumpus("สรร", "อัน"))
 # True
 
 # การตรวจสอบคำสำผัสที่ผิด
-print('เพื่อน ล้วน', kv.is_sumpus('เพื่อน', 'ล้วน'))
+print("เพื่อน ล้วน", kv.is_sumpus("เพื่อน", "ล้วน"))
 # False
 
 # การตรวจสอบคำ ครุ ลหุ
-print('สรร', kv.check_karu_lahu('สรร'))
-#karu
+print("สรร", kv.check_karu_lahu("สรร"))
+# karu
 
 # การตรวจสอบคำ ครุ ลหุ
-print('ชิชะ', kv.check_karu_lahu('ชิชะ'))
+print("ชิชะ", kv.check_karu_lahu("ชิชะ"))
 # lahu
 
 # การตรวจสอบกลอน 8 ที่ถูกฉันทลักษณ์
-print(kv.check_klon('''ณรงค์วุฒิผู้เปี่ยมวุฒิสมสง่า มากวิชาหาความรู้ไปสู่ผล
+print(
+    kv.check_klon(
+        """ณรงค์วุฒิผู้เปี่ยมวุฒิสมสง่า มากวิชาหาความรู้ไปสู่ผล
 เรื่องฟิสิกส์คณิตศาสตร์เอิร์นอดทน เล่นเกมเก่งลำดับต้นของโรงเรียน
 ต่อมาหยกธนัชพรชอบนอนหลับ แต่ผลลัพธ์คือฉลาดเรื่องอ่านเขียน
 เหมือนจะเล่นแต่เขายังพากเพียร ในการเรียนการเล่นบ้างคละกันไป
@@ -37,11 +43,16 @@
 นริศราอีฟเก่งกว่าใครเพื่อน คอยช่วยเตือนเรื่องงานคอยสั่งสอน
 อ่านตำราหาความรู้ไม่ละทอน เป็นคนดีศรีนครของจิตรลดา
 ภัสนันท์นาคลออหรือมีมี่ เรื่องเกมนี้เก่งกาจไม่กังขา
-เกมอะไรก็เล่นได้ไม่ลดวา สุดฉลาดมากปัญญามาครบครัน''', k_type=8))
+เกมอะไรก็เล่นได้ไม่ลดวา สุดฉลาดมากปัญญามาครบครัน""",
+        k_type=8,
+    )
+)
 # -> The poem is correct according to the principle.
 
 # การตรวจสอบกลอน 8 ที่ผิดฉันทลักษณ์
-print(kv.check_klon('''ณรงค์วุฒิผู้เปี่ยมวุฒิสมสง่า มากวิชาหาความรู้ไปสู่ผล
+print(
+    kv.check_klon(
+        """ณรงค์วุฒิผู้เปี่ยมวุฒิสมสง่า มากวิชาหาความรู้ไปสู่ผล
 เรื่องฟิสิกส์คณิตศาสตร์เอิร์นอดทน เล่นเกมเก่งลำดับต้นของโรงเรียน
 ต่อมาหยกธนัชพรชอบนอนหลับ แต่ผลลัพธ์คือฉลาดเรื่องอ่านเขียน
 เหมือนจะเล่นแต่เขายังพากเพียร ในการเรียนการเล่นบ้างคละกันไป
@@ -50,22 +61,39 @@
 นริศราอีฟเก่งกว่าใครเพื่อน คอยช่วยเตือนเรื่องงานคอยสั่งสอน
 อ่านตำราหาความรู้ไม่ละทอน เป็นคนดีศรีนครของจิตรลดา
 ภัสนันท์นาคลออหรือมีมี่ เรื่องเกมเอ่อเก่งกาจไม่กังขา 
-เกมอะไรก็เล่นได้ไม่ลดวา สุดฉลาดมากปัญญามาครบครัน''', k_type=8))
+เกมอะไรก็เล่นได้ไม่ลดวา สุดฉลาดมากปัญญามาครบครัน""",
+        k_type=8,
+    )
+)
 # -> ["Cant find rhyme between paragraphs ('สอน', 'ไป') in paragraph 4", "Cant find rhyme between paragraphs ('มี่', ['เกม', 'เอ่อ', 'เก่ง', 'กาจ']) in paragraph 5"]
 
 
 # การตรวจสอบกลอน 4 ที่ถูกฉันทลักษณ์
-print(kv.check_klon('''ฉันชื่อหมูกรอบ ฉันชอบกินไก่ แล้วก็วิ่งไล่ หมาชื่อนํ้าทอง ลคคนเก่ง เอ๋งเอ๋งคะนอง มีคนจับจอง เขาชื่อน้องเธียร''', k_type=4))
+print(
+    kv.check_klon(
+        """ฉันชื่อหมูกรอบ ฉันชอบกินไก่ แล้วก็วิ่งไล่ หมาชื่อนํ้าทอง ลคคนเก่ง เอ๋งเอ๋งคะนอง มีคนจับจอง เขาชื่อน้องเธียร""",
+        k_type=4,
+    )
+)
 # -> The poem is correct according to the principle.
 
 # การตรวจสอบกลอน 4 ที่ผิดฉันทลักษณ์
-print(kv.check_klon('''ฉันชื่อหมูกรอบ ฉันชอบกินไก่ แล้วก็วิ่งไล่ หมาชื่อนํ้าทอง ลคคนเก่ง เอ๋งเอ๋งเสียงหมา มีคนจับจอง เขาชื่อน้องเธียร''', k_type=4))
+print(
+    kv.check_klon(
+        """ฉันชื่อหมูกรอบ ฉันชอบกินไก่ แล้วก็วิ่งไล่ หมาชื่อนํ้าทอง ลคคนเก่ง เอ๋งเอ๋งเสียงหมา มีคนจับจอง เขาชื่อน้องเธียร""",
+        k_type=4,
+    )
+)
 # -> ["Cant find rhyme between paragraphs ('หมา', 'จอง') in paragraph 2", "Cant find rhyme between paragraphs ('หมา', 'ทอง') in paragraph 2"]
 
 # การเช็คคำเอกโท
-print(kv.check_aek_too('เอง'), kv.check_aek_too('เอ่ง'), kv.check_aek_too('เอ้ง'))
+print(
+    kv.check_aek_too("เอง"), kv.check_aek_too("เอ่ง"), kv.check_aek_too("เอ้ง")
+)
 # -> False, aek, too
-print(kv.check_aek_too(['เอง', 'เอ่ง', 'เอ้ง'])) # ใช้ List ได้เหมือนกัน
+print(kv.check_aek_too(["เอง", "เอ่ง", "เอ้ง"]))  # ใช้ List ได้เหมือนกัน
 # -> [False, 'aek', 'too']
-print(kv.check_aek_too(['ห๊ะ', 'เอ่ง', 'เอ้ง'], dead_syllable_as_aek=True)) # ใช้ List ได้เหมือนกัน และสามารถตั้งค่า ให้นับคำที่เสียงตายเป็นเอกได้ ตามการเช็คคฉันทลักษณ์กลอน
+print(
+    kv.check_aek_too(["ห๊ะ", "เอ่ง", "เอ้ง"], dead_syllable_as_aek=True)
+)  # ใช้ List ได้เหมือนกัน และสามารถตั้งค่า ให้นับคำที่เสียงตายเป็นเอกได้ ตามการเช็คคฉันทลักษณ์กลอน
 # -> ['aek', 'aek', 'too']
diff --git a/pythainlp/parse/__init__.py b/pythainlp/parse/__init__.py
index 9be9834a9..5cd6c0988 100644
--- a/pythainlp/parse/__init__.py
+++ b/pythainlp/parse/__init__.py
@@ -1,8 +1,10 @@
 # -*- coding: utf-8 -*-
 # SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
 # SPDX-License-Identifier: Apache-2.0
+
 """
 PyThaiNLP Parse
 """
 __all__ = ["dependency_parsing"]
+
 from pythainlp.parse.core import dependency_parsing
diff --git a/pythainlp/parse/core.py b/pythainlp/parse/core.py
index 1dd5d8bd2..1dcb9e4da 100644
--- a/pythainlp/parse/core.py
+++ b/pythainlp/parse/core.py
@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 # SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
 # SPDX-License-Identifier: Apache-2.0
+
 from typing import List, Union
 
 
@@ -9,7 +10,7 @@
 
 
 def dependency_parsing(
-    text: str, model: str = None, tag: str = "str", engine: str = "esupar"
+    text: str, model: str = "", tag: str = "str", engine: str = "esupar"
 ) -> Union[List[List[str]], str]:
     """
     Dependency Parsing
@@ -92,6 +93,7 @@ def dependency_parsing(
         # 3       คนดี             NOUN    NCMN    _       2       obj     _       SpaceAfter=No
     """
     global _tagger, _tagger_name
+
     if _tagger_name != engine:
         if engine == "esupar":
             from pythainlp.parse.esupar_engine import Parse
@@ -111,5 +113,7 @@ def dependency_parsing(
             _tagger = Parse(model=model)
         else:
             raise NotImplementedError("The engine doesn't support.")
+
     _tagger_name = engine
+
     return _tagger(text, tag=tag)
diff --git a/pythainlp/parse/spacy_thai_engine.py b/pythainlp/parse/spacy_thai_engine.py
index dabf4caeb..6d0eef7ab 100644
--- a/pythainlp/parse/spacy_thai_engine.py
+++ b/pythainlp/parse/spacy_thai_engine.py
@@ -3,8 +3,10 @@
 spacy_thai: Tokenizer, POS tagger, and dependency parser for the Thai language using Universal Dependencies.
 
 GitHub: https://github.com/KoichiYasuoka/spacy-thai
+
 """
 from typing import List, Union
+
 import spacy_thai
 
 
diff --git a/pythainlp/parse/transformers_ud.py b/pythainlp/parse/transformers_ud.py
index 2adfe2849..9d1ffca5b 100644
--- a/pythainlp/parse/transformers_ud.py
+++ b/pythainlp/parse/transformers_ud.py
@@ -12,14 +12,15 @@
 """
 import os
 from typing import List, Union
+
 import numpy
 import torch
 import ufal.chu_liu_edmonds
 from transformers import (
-    AutoTokenizer,
+    AutoConfig,
     AutoModelForQuestionAnswering,
     AutoModelForTokenClassification,
-    AutoConfig,
+    AutoTokenizer,
     TokenClassificationPipeline,
 )
 from transformers.utils import cached_file
@@ -35,8 +36,9 @@ def __init__(
         self.model = AutoModelForQuestionAnswering.from_pretrained(model)
         x = AutoModelForTokenClassification.from_pretrained
         if os.path.isdir(model):
-            d, t = x(os.path.join(model, "deprel")), x(
-                os.path.join(model, "tagger")
+            d, t = (
+                x(os.path.join(model, "deprel")),
+                x(os.path.join(model, "tagger")),
             )
         else:
             c = AutoConfig.from_pretrained(
@@ -61,11 +63,13 @@ def __call__(
             (t["start"], t["end"], t["entity_group"])
             for t in self.deprel(text)
         ]
-        z, n = {
-            t["start"]: t["entity"].split("|") for t in self.tagger(text)
-        }, len(w)
-        r, m = [text[s:e] for s, e, p in w], numpy.full(
-            (n + 1, n + 1), numpy.nan
+        z, n = (
+            {t["start"]: t["entity"].split("|") for t in self.tagger(text)},
+            len(w),
+        )
+        r, m = (
+            [text[s:e] for s, e, p in w],
+            numpy.full((n + 1, n + 1), numpy.nan),
         )
         v, c = self.tokenizer(r, add_special_tokens=False)["input_ids"], []
         for i, t in enumerate(v):
diff --git a/pythainlp/parse/ud_goeswith.py b/pythainlp/parse/ud_goeswith.py
index eb9b27810..fc258d41d 100644
--- a/pythainlp/parse/ud_goeswith.py
+++ b/pythainlp/parse/ud_goeswith.py
@@ -11,10 +11,11 @@
 GitHub: https://github.com/KoichiYasuoka
 """
 from typing import List, Union
-from transformers import AutoTokenizer, AutoModelForTokenClassification
+
 import numpy as np
 import torch
 import ufal.chu_liu_edmonds
+from transformers import AutoModelForTokenClassification, AutoTokenizer
 
 
 class Parse:
@@ -27,21 +28,20 @@ def __init__(
         self.model = AutoModelForTokenClassification.from_pretrained(model)
 
     def __call__(
-        self,
-        text: str, tag: str = "str"
+        self, text: str, tag: str = "str"
     ) -> Union[List[List[str]], str]:
         w = self.tokenizer(text, return_offsets_mapping=True)
         v = w["input_ids"]
         x = [
-            v[0:i] + [self.tokenizer.mask_token_id] + v[i + 1:] + [j]
+            v[0:i] + [self.tokenizer.mask_token_id] + v[i + 1 :] + [j]
             for i, j in enumerate(v[1:-1], 1)
         ]
         with torch.no_grad():
-            e = self.model(input_ids=torch.tensor(x)
-                           ).logits.numpy()[:, 1:-2, :]
+            e = self.model(input_ids=torch.tensor(x)).logits.numpy()[
+                :, 1:-2, :
+            ]
         r = [
-            1 if i == 0 else -1
-            if j.endswith("|root") else 0
+            1 if i == 0 else -1 if j.endswith("|root") else 0
             for i, j in sorted(self.model.config.id2label.items())
         ]
         e += np.where(np.add.outer(np.identity(e.shape[0]), r) == 0, 0, np.nan)
@@ -60,8 +60,10 @@ def __call__(
         h = ufal.chu_liu_edmonds.chu_liu_edmonds(m)[0]
         if [0 for i in h if i == 0] != [0]:
             m[:, 0] += np.where(
-                m[:, 0] == np.nanmax(
-                    m[[i for i, j in enumerate(h) if j == 0], 0]), 0, np.nan
+                m[:, 0]
+                == np.nanmax(m[[i for i, j in enumerate(h) if j == 0], 0]),
+                0,
+                np.nan,
             )
             m[[i for i, j in enumerate(h) if j == 0]] += [
                 0 if i == 0 or j == 0 else np.nan for i, j in enumerate(h)
@@ -84,21 +86,30 @@ def __call__(
                         str(h[i]),
                         q[-1],
                         "_",
-                        "_" if i < len(v) and e < v[i][0] else "SpaceAfter=No"
+                        "_" if i < len(v) and e < v[i][0] else "SpaceAfter=No",
                     ]
                 )
             return _tag_data
         else:
             for i, (s, e) in enumerate(v, 1):
                 q = self.model.config.id2label[p[i, h[i]]].split("|")
-                u += "\t".join([str(i),
-                                text[s:e],
-                                "_",
-                                q[0],
-                                "_",
-                                "|".join(q[1:-1]),
-                                str(h[i]),
-                                q[-1],
-                                "_",
-                                "_" if i < len(v) and e < v[i][0] else "SpaceAfter=No"]) + "\n"
+                u += (
+                    "\t".join(
+                        [
+                            str(i),
+                            text[s:e],
+                            "_",
+                            q[0],
+                            "_",
+                            "|".join(q[1:-1]),
+                            str(h[i]),
+                            q[-1],
+                            "_",
+                            "_"
+                            if i < len(v) and e < v[i][0]
+                            else "SpaceAfter=No",
+                        ]
+                    )
+                    + "\n"
+                )
             return u + "\n"
diff --git a/pythainlp/phayathaibert/__init__.py b/pythainlp/phayathaibert/__init__.py
index bf0f847bf..537de7706 100644
--- a/pythainlp/phayathaibert/__init__.py
+++ b/pythainlp/phayathaibert/__init__.py
@@ -1,6 +1,11 @@
 # -*- coding: utf-8 -*-
 # SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
 # SPDX-License-Identifier: Apache-2.0
+
+"""
+PhayaThaiBERT
+"""
+
 __all__ = [
     "NamedEntityTagger",
     "PartOfSpeechTagger",
diff --git a/pythainlp/phayathaibert/core.py b/pythainlp/phayathaibert/core.py
index 579d24ddc..c4498799a 100644
--- a/pythainlp/phayathaibert/core.py
+++ b/pythainlp/phayathaibert/core.py
@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 # SPDX-FileCopyrightText: Copyright 2016-2023 PyThaiNLP Project
 # SPDX-License-Identifier: Apache-2.0
+
 from typing import Callable, Collection, List, Tuple, Union
 import random
 import re
@@ -18,19 +19,24 @@
 
 class ThaiTextProcessor:
     def __init__(self):
-        self._TK_UNK, self._TK_REP, self._TK_WREP, self._TK_URL, self._TK_END = \
-            "<unk> <rep> <wrep> <url> </s>".split()
+        (
+            self._TK_UNK,
+            self._TK_REP,
+            self._TK_WREP,
+            self._TK_URL,
+            self._TK_END,
+        ) = "<unk> <rep> <wrep> <url> </s>".split()
         self.SPACE_SPECIAL_TOKEN = "<_>"
 
     def replace_url(self, text: str) -> str:
         """
-            Replace url in `text` with TK_URL (https://stackoverflow.com/a/6041965)
-            :param str text: text to replace url
-            :return: text where urls  are replaced
-            :rtype: str
-            :Example:
-                >>> replace_url("go to https://github.com")
-                go to <url>
+        Replace url in `text` with TK_URL (https://stackoverflow.com/a/6041965)
+        :param str text: text to replace url
+        :return: text where urls  are replaced
+        :rtype: str
+        :Example:
+            >>> replace_url("go to https://github.com")
+            go to <url>
         """
         URL_PATTERN = \
             r"(http|ftp|https)://([\w_-]+(?:(?:\.[\w_-]+)+))([\w.,@?^=%&:/~+#-]*[\w@?^=%&/~+#-])?"
@@ -38,13 +44,13 @@ def replace_url(self, text: str) -> str:
 
     def rm_brackets(text: str) -> str:
         """
-            Remove all empty brackets and artifacts within brackets from `text`.
-            :param str text: text to remove useless brackets
-            :return: text where all useless brackets are removed
-            :rtype: str
-            :Example:
-                >>> rm_brackets("hey() whats[;] up{*&} man(hey)")
-                hey whats up man(hey)
+        Remove all empty brackets and artifacts within brackets from `text`.
+        :param str text: text to remove useless brackets
+        :return: text where all useless brackets are removed
+        :rtype: str
+        :Example:
+            >>> rm_brackets("hey() whats[;] up{*&} man(hey)")
+            hey whats up man(hey)
         """
         # remove empty brackets
         new_line = re.sub(r"\(\)", "", text)
@@ -55,49 +61,61 @@ def rm_brackets(text: str) -> str:
         new_line = re.sub(r"\{[^a-zA-Z0-9ก-๙]+\}", "", new_line)
         new_line = re.sub(r"\[[^a-zA-Z0-9ก-๙]+\]", "", new_line)
         # artifiacts after (
-        new_line = re.sub(r"(?<=\()[^a-zA-Z0-9ก-๙]+(?=[a-zA-Z0-9ก-๙])", "", new_line)
-        new_line = re.sub(r"(?<=\{)[^a-zA-Z0-9ก-๙]+(?=[a-zA-Z0-9ก-๙])", "", new_line)
-        new_line = re.sub(r"(?<=\[)[^a-zA-Z0-9ก-๙]+(?=[a-zA-Z0-9ก-๙])", "", new_line)
+        new_line = re.sub(
+            r"(?<=\()[^a-zA-Z0-9ก-๙]+(?=[a-zA-Z0-9ก-๙])", "", new_line
+        )
+        new_line = re.sub(
+            r"(?<=\{)[^a-zA-Z0-9ก-๙]+(?=[a-zA-Z0-9ก-๙])", "", new_line
+        )
+        new_line = re.sub(
+            r"(?<=\[)[^a-zA-Z0-9ก-๙]+(?=[a-zA-Z0-9ก-๙])", "", new_line
+        )
         # artifacts before )
-        new_line = re.sub(r"(?<=[a-zA-Z0-9ก-๙])[^a-zA-Z0-9ก-๙]+(?=\))", "", new_line)
-        new_line = re.sub(r"(?<=[a-zA-Z0-9ก-๙])[^a-zA-Z0-9ก-๙]+(?=\})", "", new_line)
-        new_line = re.sub(r"(?<=[a-zA-Z0-9ก-๙])[^a-zA-Z0-9ก-๙]+(?=\])", "", new_line)
+        new_line = re.sub(
+            r"(?<=[a-zA-Z0-9ก-๙])[^a-zA-Z0-9ก-๙]+(?=\))", "", new_line
+        )
+        new_line = re.sub(
+            r"(?<=[a-zA-Z0-9ก-๙])[^a-zA-Z0-9ก-๙]+(?=\})", "", new_line
+        )
+        new_line = re.sub(
+            r"(?<=[a-zA-Z0-9ก-๙])[^a-zA-Z0-9ก-๙]+(?=\])", "", new_line
+        )
         return new_line
 
     def replace_newlines(text: str) -> str:
         """
-            Replace newlines in `text` with spaces.
-            :param str text: text to replace all newlines with spaces
-            :return: text where all newlines are replaced with spaces
-            :rtype: str
-            :Example:
-                >>> rm_useless_spaces("hey whats\n\nup")
-                hey whats  up
+        Replace newlines in `text` with spaces.
+        :param str text: text to replace all newlines with spaces
+        :return: text where all newlines are replaced with spaces
+        :rtype: str
+        :Example:
+            >>> rm_useless_spaces("hey whats\n\nup")
+            hey whats  up
         """
 
         return re.sub(r"[\n]", " ", text.strip())
 
     def rm_useless_spaces(text: str) -> str:
         """
-            Remove multiple spaces in `text`. (code from `fastai`)
-            :param str text: text to replace useless spaces
-            :return: text where all spaces are reduced to one
-            :rtype: str
-            :Example:
-                >>> rm_useless_spaces("oh         no")
-                oh no
+        Remove multiple spaces in `text`. (code from `fastai`)
+        :param str text: text to replace useless spaces
+        :return: text where all spaces are reduced to one
+        :rtype: str
+        :Example:
+            >>> rm_useless_spaces("oh         no")
+            oh no
         """
         return re.sub(" {2,}", " ", text)
 
     def replace_spaces(text: str, space_token: str = "<_>") -> str:
         """
-            Replace spaces with _
-            :param str text: text to replace spaces
-            :return: text where all spaces replaced with _
-            :rtype: str
-            :Example:
-                >>> replace_spaces("oh no")
-                oh_no
+        Replace spaces with _
+        :param str text: text to replace spaces
+        :return: text where all spaces replaced with _
+        :rtype: str
+        :Example:
+            >>> replace_spaces("oh no")
+            oh_no
         """
         return re.sub(" ", space_token, text)
 
@@ -144,6 +162,7 @@ def replace_wrep_post(self, toks: Collection[str]) -> Collection[str]:
             else:
                 res.append(previous_word)
             previous_word = current_word
+
         return res[1:]
 
     def remove_space(toks: Collection[str]) -> Collection[str]:
@@ -162,6 +181,7 @@ def remove_space(toks: Collection[str]) -> Collection[str]:
             t = t.strip()
             if t:
                 res.append(t)
+
         return res
 
     # combine them together
@@ -181,48 +201,58 @@ def preprocess(
         for rule in pre_rules:
             text = rule(text)
         toks = tok_func(text)
+
         return "".join(toks)
 
 
 class ThaiTextAugmenter:
     def __init__(self) -> None:
-        from transformers import (AutoTokenizer,
-                                  AutoModelForMaskedLM,
-                                  pipeline,)
+        from transformers import (
+            AutoModelForMaskedLM,
+            AutoTokenizer,
+            pipeline,
+        )
+
         self.tokenizer = AutoTokenizer.from_pretrained(_model_name)
-        self.model_for_masked_lm = AutoModelForMaskedLM.from_pretrained(_model_name)
-        self.model = pipeline("fill-mask",
-                              tokenizer=self.tokenizer,
-                              model=self.model_for_masked_lm,
-                              )
+        self.model_for_masked_lm = AutoModelForMaskedLM.from_pretrained(
+            _model_name
+        )
+        self.model = pipeline(
+            "fill-mask",
+            tokenizer=self.tokenizer,
+            model=self.model_for_masked_lm,
+        )
         self.processor = ThaiTextProcessor()
 
-    def generate(self,
-                 sample_text: str,
-                 word_rank: int,
-                 max_length: int = 3,
-                 sample: bool = False,
-                 ) -> str:
+    def generate(
+        self,
+        sample_text: str,
+        word_rank: int,
+        max_length: int = 3,
+        sample: bool = False,
+    ) -> str:
         sample_txt = sample_text
         final_text = ""
         for j in range(max_length):
             input = self.processor.preprocess(sample_txt)
             if sample:
                 random_word_idx = random.randint(0, 4)
-                output = self.model(input)[random_word_idx]['sequence']
+                output = self.model(input)[random_word_idx]["sequence"]
             else:
-                output = self.model(input)[word_rank]['sequence']
+                output = self.model(input)[word_rank]["sequence"]
             sample_txt = output + "<mask>"
             final_text = sample_txt
 
         gen_txt = re.sub("<mask>", "", final_text)
+
         return gen_txt
 
-    def augment(self,
-                text: str,
-                num_augs: int = 3,
-                sample: bool = False,
-                ) -> List[str]:
+    def augment(
+        self,
+        text: str,
+        num_augs: int = 3,
+        sample: bool = False,
+    ) -> List[str]:
         """
         Text Augment from phayathaibert
 
@@ -248,80 +278,96 @@ def augment(self,
                 'ช้างมีทั้งหมด 50 ตัว บนดวงจันทร์.‼',
                 'ช้างมีทั้งหมด 50 ตัว บนเขาค่ะ😁']
         """
+        MAX_NUM_AUGS = 5
         augment_list = []
-        if num_augs <= 5:
+
+        if num_augs <= MAX_NUM_AUGS:
             for rank in range(num_augs):
-                gen_text = self.generate(text,
-                                         rank,
-                                         sample=sample,
-                                         )
-                processed_text = re.sub("<_>", " ", self.processor.preprocess(gen_text))
+                gen_text = self.generate(
+                    text,
+                    rank,
+                    sample=sample,
+                )
+                processed_text = re.sub(
+                    "<_>", " ", self.processor.preprocess(gen_text)
+                )
                 augment_list.append(processed_text)
+        else:
+            raise ValueError(
+                f"augmentation of more than {num_augs} is exceeded the default limit: {MAX_NUM_AUGS}"
+            )
 
-            return augment_list
+        return augment_list
 
 
 class PartOfSpeechTagger:
     def __init__(self, model: str = "lunarlist/pos_thai_phayathai") -> None:
         # Load model directly
-        from transformers import (AutoTokenizer,
-                                  AutoModelForTokenClassification,
-                                  )
+        from transformers import (
+            AutoTokenizer,
+            AutoModelForTokenClassification,
+        )
+
         self.tokenizer = AutoTokenizer.from_pretrained(model)
         self.model = AutoModelForTokenClassification.from_pretrained(model)
 
-    def get_tag(self,
-                sentence: str,
-                strategy: str = 'simple'
-                ) -> List[List[Tuple[str, str]]]:
+    def get_tag(
+        self, sentence: str, strategy: str = "simple"
+    ) -> List[List[Tuple[str, str]]]:
         """
-    Marks sentences with part-of-speech (POS) tags.
+        Marks sentences with part-of-speech (POS) tags.
 
-    :param str sentence: a list of lists of tokenized words
-    :return: a list of lists of tuples (word, POS tag)
-    :rtype: list[list[tuple[str, str]]]
+        :param str sentence: a list of lists of tokenized words
+        :return: a list of lists of tuples (word, POS tag)
+        :rtype: list[list[tuple[str, str]]]
 
-    :Example:
+        :Example:
 
-    Labels POS for given sentence::
+        Labels POS for given sentence::
 
-        from pythainlp.phayathaibert.core import PartOfSpeechTagger
+            from pythainlp.phayathaibert.core import PartOfSpeechTagger
 
-        tagger = PartOfSpeechTagger()
-        tagger.get_tag("แมวทำอะไรตอนห้าโมงเช้า")
-        # output:
-        # [[('แมว', 'NOUN'), ('ทําอะไร', 'VERB'), ('ตอนห้าโมงเช้า', 'NOUN')]]
+            tagger = PartOfSpeechTagger()
+            tagger.get_tag("แมวทำอะไรตอนห้าโมงเช้า")
+            # output:
+            # [[('แมว', 'NOUN'), ('ทําอะไร', 'VERB'), ('ตอนห้าโมงเช้า', 'NOUN')]]
         """
         from transformers import TokenClassificationPipeline
-        pipeline = TokenClassificationPipeline(model=self.model,
-                                               tokenizer=self.tokenizer,
-                                               aggregation_strategy=strategy,
-                                               )
+
+        pipeline = TokenClassificationPipeline(
+            model=self.model,
+            tokenizer=self.tokenizer,
+            aggregation_strategy=strategy,
+        )
         outputs = pipeline(sentence)
-        word_tags = [[(tag['word'], tag['entity_group']) for tag in outputs]]
+        word_tags = [[(tag["word"], tag["entity_group"]) for tag in outputs]]
+
         return word_tags
 
 
 class NamedEntityTagger:
     def __init__(self, model: str = "Pavarissy/phayathaibert-thainer") -> None:
-        from transformers import (AutoTokenizer,
-                                  AutoModelForTokenClassification,
-                                  )
+        from transformers import (
+            AutoTokenizer,
+            AutoModelForTokenClassification,
+        )
+
         self.tokenizer = AutoTokenizer.from_pretrained(model)
         self.model = AutoModelForTokenClassification.from_pretrained(model)
 
-    def get_ner(self,
-                text: str,
-                tag: bool = False,
-                pos: bool = False,
-                strategy: str = "simple",
-                ) -> Union[List[Tuple[str, str]], List[Tuple[str, str, str]], str]:
+    def get_ner(
+        self,
+        text: str,
+        tag: bool = False,
+        pos: bool = False,
+        strategy: str = "simple",
+    ) -> Union[List[Tuple[str, str]], List[Tuple[str, str, str]], str]:
         """
         This function tags named entities in text in IOB format.
 
         :param str text: text in Thai to be tagged
         :param bool pos: output with part-of-speech tags.\
-            (phayathaibert is supported in PartOfSpeechTagger)
+            (PhayaThaiBERT is supported in PartOfSpeechTagger)
         :return: a list of tuples associated with tokenized words, NER tags,
                  POS tags (if the parameter `pos` is specified as `True`),
                  and output HTML-like tags (if the parameter `tag` is
@@ -343,41 +389,56 @@ def get_ner(self,
                 <LOCATION>จาก</LOCATION><LOCATION>ประเทศไทย</LOCATION>'
         """
         from transformers import TokenClassificationPipeline
+
         if pos:
-            warnings.warn("This model doesn't support output \
-                          postag and It doesn't output the postag.")
+            warnings.warn(
+                "This model doesn't support output \
+                          postag and It doesn't output the postag."
+            )
+
         sample_output = []
         tag_text_list = []
         current_pos = 0
-        pipeline = TokenClassificationPipeline(model=self.model,
-                                               tokenizer=self.tokenizer,
-                                               aggregation_strategy=strategy,
-                                               )
+        pipeline = TokenClassificationPipeline(
+            model=self.model,
+            tokenizer=self.tokenizer,
+            aggregation_strategy=strategy,
+        )
         outputs = pipeline(text)
+
         for token in outputs:
-            ner_tag = token['entity_group']
-            begin_pos, end_pos = token['start'], token['end']
+            ner_tag = token["entity_group"]
+            begin_pos, end_pos = token["start"], token["end"]
             if current_pos == 0:
-                text_tag = text[:begin_pos] + f"<{ner_tag}>" \
-                    + text[begin_pos:end_pos] + f"</{ner_tag}>"
+                text_tag = (
+                    text[:begin_pos]
+                    + f"<{ner_tag}>"
+                    + text[begin_pos:end_pos]
+                    + f"</{ner_tag}>"
+                )
             else:
-                text_tag = text[current_pos:begin_pos] + f"<{ner_tag}>" \
-                    + text[begin_pos:end_pos] + f"</{ner_tag}>"
+                text_tag = (
+                    text[current_pos:begin_pos]
+                    + f"<{ner_tag}>"
+                    + text[begin_pos:end_pos]
+                    + f"</{ner_tag}>"
+                )
             tag_text_list.append(text_tag)
-            sample_output.append((token['word'], token['entity_group']))
+            sample_output.append((token["word"], token["entity_group"]))
             current_pos = end_pos
+
         if tag:
             return str("".join(tag_text_list))
-        else:
-            return sample_output
+
+        return sample_output
 
 
 def segment(sentence: str) -> List[str]:
     """
-    Subword tokenize of phayathaibert, \
-    sentencepiece from wangchanberta model with Vocabulary Expansion.
+    Subword tokenize of PhayaThaiBERT, \
+    sentencepiece from WangchanBERTa model with vocabulary expansion.
 
-    :param str text: text to be tokenized
+    :param str sentence: text to be tokenized
     :return: list of subwords
     :rtype: list[str]
     """