def __init__(self, name="MianBot"):
self.name = name # The name of chatbot.
self.speech = '' # The lastest user's input
self.speech_domain = '' # The domain of speech.
self.speech_matchee = '' # The matchee term of speech.
self.speech_path = None # The classification tree traveling path of speech.
self.speech_seg = []
self.root_domain = None # The root domain of user's input.
self.domain_similarity = 0.0 # The similarity between domain and speech.
cur_dir = os.getcwd()
os.chdir(os.path.dirname(__file__))
self.extract_attr_log = open('log/extract_arrt.log',
'w',
encoding='utf-8')
self.exception_log = open('log/exception.log', 'w', encoding='utf-8')
os.chdir(cur_dir)
# For rule matching
self.console = console.Console(model_path="model/ch-corpus-3sg.bin")
self.custom_rulebase = crb.CustomRuleBase() # for one time matching.
self.custom_rulebase.model = self.console.rb.model # pass word2vec model
# For QA
self.github_qa_unupdated = True
if not self.github_qa_unupdated:
self.answerer = qa.Answerer()
self.default_response = ["是嗎?", "我不太明白你的意思", "原來如此"]
def __init__(self,
name="MianBot",
build_console=True,
w2v_model_path="model/ch-corpus-3sg.bin"):
"""
# Args:
- build_console: whether to construct topic matching based on word vectors console,
如果只需要 qa 模組，可將 build_console 關閉，可見 demo_qa.py
"""
self.name = name # The name of chatbot.
self.speech = '' # The lastest user's input
self.speech_domain = '' # The domain of speech.
self.speech_matchee = '' # The matchee term of speech.
self.speech_path = None # The classification tree traveling path of speech.
self.speech_seg = []
self.root_domain = None # The root domain of user's input.
self.domain_similarity = 0.0 # The similarity between domain and speech.
cur_dir = os.getcwd()
os.chdir(os.path.dirname(__file__))
self.extract_attr_log = open('log/extract_arrt.log',
'w',
encoding='utf-8')
self.exception_log = open('log/exception.log', 'w', encoding='utf-8')
os.chdir(cur_dir)
# For rule matching
if build_console:
self.console = console.Console(model_path=w2v_model_path)
# self.custom_rulebase = crb.CustomRuleBase() # for one time matching.
# self.custom_rulebase.model = self.console.rb.model # pass word2vec model
# For Question Answering
self.github_qa_unupdated = False
if not self.github_qa_unupdated:
try:
self.answerer = qa.Answerer()
except Exception as exc:
print(
"[QA] Please confirm the directory structure of the questions and answer data set is correct."
)
print(
"[QA] If you are still getting errors,s change self.github_qa_unupdated to True"
)
self.default_response = [
"Say it again?", "I did not catch that.",
"I do not know what you mean.", "Huh?"
]
def __init__(self,
name="阿母",
build_console=True,
w2v_model_path="model/ch-corpus-3sg.bin"):
"""
# Args:
- build_console: 是否要建構依照詞向量進行主題匹配的 console,
如果只需要 qa 模組，可將 build_console 關閉，可見 demo_qa.py
"""
self.name = name # The name of chatbot.
self.speech = '' # The lastest user's input
self.speech_domain = '' # The domain of speech.
self.speech_matchee = '' # The matchee term of speech.
self.speech_path = None # The classification tree traveling path of speech.
self.speech_seg = []
self.root_domain = None # The root domain of user's input.
self.domain_similarity = 0.0 # The similarity between domain and speech.
cur_dir = os.getcwd()
os.chdir(os.path.dirname(__file__))
self.extract_attr_log = open('log/extract_arrt.log',
'w',
encoding='utf-8')
self.exception_log = open('log/exception.log', 'w', encoding='utf-8')
os.chdir(cur_dir)
# For rule matching
if build_console:
self.console = console.Console(model_path=w2v_model_path)
# self.custom_rulebase = crb.CustomRuleBase() # for one time matching.
# self.custom_rulebase.model = self.console.rb.model # pass word2vec model
# For Question Answering
self.github_qa_unupdated = False
if not self.github_qa_unupdated:
try:
self.answerer = qa.Answerer()
except Exception as exc:
print("[QA] 請確認問答資料集的目錄結構是否正確")
print(
"[QA] 如尚未取得問答資料集, 請至 Github: zake7749/Chatbot/Readme.md 中下載, 或將 self.github_qa_unupdated 設為 true"
)
self.default_response = [
"是嗎?", "我不太明白你的意思", "原來如此", "可以再說一次嗎", "不要滑手機了快去養成習慣"
]
