feat: add zh-cn, zh-tw support

README.md

@@ -11,7 +11,7 @@ Whether you are new to the process and are building your first AI assistant or y
 - Why is the assistant responding incorrectly to this question?
 - How do I improve my assistant’s ability to understand questions?
 
-Currently Supported Languages: en, fr, cs, de, es, it, pt, nl
+Currently Supported Languages: en, fr, cs, de, es, it, pt, nl, zh-cn, zh-tw
 
 ## Usage
 If you clone the notebook from this repository locally, please use the steps below. For usage in Watson studio, please refer to the 

assistant_skill_analysis/resources/zh-cn/stopwords

@@ -0,0 +1,155 @@
+<
+>
+|
+-
+,
+;
+:
+!
+?
+.
+''
+'
+"
+(
+)
+[
+]
+{
+}
+*
+%
++
+。
+<SE>
+一
+一会儿
+一边
+一面
+上
+下
+不
+不但
+不光
+不可
+不如
+不是
+不管
+不论
+与
+与其
+个
+中
+为
+之
+之所以
+也
+也不
+也许
+也许是
+了
+于
+从
+他
+他们
+以
+会
+但
+你们
+便
+倘若
+先
+全
+其
+再
+到
+前
+十
+即使
+却
+又
+及
+只
+只有
+只要
+可
+可以
+可是
+可能
+各
+后
+向
+和
+哪怕
+因为
+因此
+在
+地
+多
+她
+她们
+如果
+宁可
+它
+它们
+对
+将
+小
+就
+尽管
+已
+已经
+并
+并且
+很
+我
+我们
+或
+所
+所以
+才
+把
+据
+无论
+既
+既然
+时
+是
+是因为
+更
+最
+有
+未
+来
+此
+每
+没有
+然后
+然而
+用
+由
+由于
+的
+看
+着
+种
+而
+而且
+而是
+能
+自己
+至
+虽然
+被
+要
+认为
+让
+该
+还
+还是
+这
+通过
+那么
+都
+非
+、

assistant_skill_analysis/resources/zh-tw/stopwords

@@ -0,0 +1,51 @@
+the
+of
+is
+and
+to
+in
+that
+we
+for
+an
+are
+by
+be
+as
+on
+with
+can
+if
+from
+which
+you
+it
+this
+then
+at
+have
+all
+not
+one
+has
+or
+that
+的
+了
+和
+是
+就
+都
+而
+及
+與
+著
+或
+一個
+沒有
+我們
+你們
+妳們
+他們
+她們
+是否

assistant_skill_analysis/utils/lang_utils.py

@@ -1,20 +1,31 @@
 import os
 import re
+from types import SimpleNamespace
 import sys
+import jieba
 from nltk.stem.snowball import SnowballStemmer
 from spacy.tokenizer import Tokenizer
 import unicodedata
 import assistant_skill_analysis
 
 
-SUPPORTED_LANGUAGE = ["en", "fr", "de", "cs", "es", "it", "pt", "nl"]
+SUPPORTED_LANGUAGE = ["en", "fr", "de", "cs", "es", "it", "pt", "nl", "zh-cn", "zh-tw"]
 PUNCTUATION = [
     "\\" + chr(i)
     for i in range(sys.maxunicode)
     if unicodedata.category(chr(i)).startswith("P")
 ]
 
 
+class _JiebaTokenizerWrapper:
+    """for zh-cn and zh-tw"""
+
+    def __call__(self, *args, **kwargs):
+        text = args[0]
+        for token in jieba.tokenize(text):
+            yield SimpleNamespace(text=token[0])
+
+
 class LanguageUtility:
     def __init__(self, language_code):
         if language_code not in SUPPORTED_LANGUAGE:
@@ -96,6 +107,11 @@ def init_resources(self):
             self.tokenizer = Tokenizer(Dutch().vocab)
             self.stemmer = SnowballStemmer(language="dutch")
             self.stop_words = self.load_stop_words(stopwords_path)
+
+        elif self.language_code in ["zh-cn", "zh-tw"]:
+            self.tokenizer = _JiebaTokenizerWrapper()
+            self.stop_words = self.load_stop_words(stopwords_path)
+
         else:
             raise Exception("language code %s is not supported", self.language_code)
 

assistant_skill_analysis/utils/parse_secret.py

@@ -3,6 +3,7 @@
 WA_SECRETS = ["WA_CONFIG", "WA_CONFIG_ACTION"]
 
 if __name__ == "__main__":
+    raise ValueError(len(str(os.environ["WA_CONFIG"]).strip()))
     for secret in WA_SECRETS:
         entry = os.environ[secret]
         with open("./" + secret.lower() + ".txt", "w", encoding="utf-8") as f:

classic_dialog_skill_analysis.ipynb

@@ -73,7 +73,7 @@
    "metadata": {},
    "source": [
     "Pick the language code correspond to your workspace data:   \n",
-    "*Supported Language codes:* **en, fr, de, es, cs, it, pt, nl**"
+    "*Supported Language codes:* **en, fr, de, es, cs, it, pt, nl, zh-cn, zh-tw**"
    ]
   },
   {

classic_dialog_skill_analysis_cp4d.ipynb

@@ -73,7 +73,7 @@
    "metadata": {},
    "source": [
     "Pick the language code correspond to your workspace data:   \n",
-    "*Supported Language codes:* **en, fr, de, es, cs, it, pt, nl**"
+    "*Supported Language codes:* **en, fr, de, es, cs, it, pt, nl, zh-cn, zh-tw**"
    ]
   },
   {

new_experience_skill_analysis.ipynb

@@ -80,7 +80,7 @@
     "### Assistant Settings\n",
     "Please set values for the variables in the cell below to configure this notebook.\n",
     "\n",
-    "- **LANGUAGE_CODE:** language code correspond to your workspace data, supported languages: **en, fr, de, es, cs, it, pt, nl**\n",
+    "- **LANGUAGE_CODE:** language code correspond to your workspace data, supported languages: **en, fr, de, es, cs, it, pt, nl, zh-cn, zh-tw**\n",
     "\n",
     "- **ASSISTANT_ID:** id of the Watson Assistant service instance\n",
     "\n",

new_experience_skill_analysis_cp4d.ipynb

@@ -80,7 +80,7 @@
     "### Assistant Settings\n",
     "Please set values for the variables in the cell below to configure this notebook. The notebook uses CloudPakForDataAuthenticator to authenticate the APIs.\n",
     "\n",
-    "- **LANGUAGE_CODE:** language code correspond to your workspace data, supported languages: **en, fr, de, es, cs, it, pt, nl**\n",
+    "- **LANGUAGE_CODE:** language code correspond to your workspace data, supported languages: **en, fr, de, es, cs, it, pt, nl, zh-cn, zh-tw**\n",
     "\n",
     "- **ASSISTANT_ID:** id of the Watson Assistant service instance\n",
     "\n",

requirements.txt

@@ -11,4 +11,5 @@ scipy>=1.2.0
 jupyter
 spacy~=2.3.2
 ibm-cos-sdk>=2.11.0
-nbconvert>=7.7.1
+nbconvert>=7.7.1
+jieba

tests/end2end/end2end_test.py

@@ -8,7 +8,7 @@ def setUpClass(cls):
         # points to dev010_Haode-Qi
         CONFIG_FILE = "./wa_config.txt"
         with open(CONFIG_FILE) as fi:
-            cls.apikey = fi.readline().strip()
+            cls.apikey = fi.read()#fi.readline().strip()
 
         with open(
             "tests/resources/test_workspaces/skill-Customer-Care-Sample.json",
@@ -24,6 +24,7 @@ def setUpClass(cls):
             authenticator_url=authenticator_url,
             api_version=skills_util.DEFAULT_V1_API_VERSION,
         )
+        raise ValueError("api:"+str(cls.apikey)+",url:"+str(URL)+",auth:"+str(authenticator_url))
         cls.wksp_id = skills_util.get_test_workspace(
             conversation=cls.conversation, workspace_json=data
         )

tests/utils/test_lang_utils.py

@@ -61,6 +61,20 @@ def test_de(self):
         sent = util.tokenize(sent)
         self.assertEqual(sent, ["autobahn"])
 
+    def test_zh_cn(self):
+        util = LanguageUtility("zh-cn")
+        sent = util.preprocess("不想当兼职")
+        self.assertEqual(sent, "不想当兼职")
+        sent = util.tokenize(sent)
+        self.assertEqual(sent, ['不想', '当', '兼职'])
+
+    def test_zh_tw(self):
+        util = LanguageUtility("zh-tw")
+        sent = util.preprocess("畀到機會我嘗試")
+        self.assertEqual(sent, "畀到機會我嘗試")
+        sent = util.tokenize(sent)
+        self.assertEqual(sent, ['畀', '到', '機會', '我', '嘗試'])
+
     def tearDown(self):
         unittest.TestCase.tearDown(self)
         self.skill_file.close()