1 files changed, 0 insertions, 55 deletions
diff --git a/ATRI/plugins/atri_chat_bot.py b/ATRI/plugins/atri_chat_bot.py
deleted file mode 100644
index 3226b2f..0000000
--- a/ATRI/plugins/atri_chat_bot.py
+++ /dev/null
@@ -1,55 +0,0 @@
-from ATRI.config import ChatterBot
-from chatterbot import ChatBot
-from chatterbot.trainers import ListTrainer
-from chatterbot.trainers import ChatterBotCorpusTrainer
-from ATRI.log import logger as log
-
-__doc__ = """
-可以不断学习的聊天(胡言乱语/复读)机器人
-https://chatterbot.readthedocs.io/
-"""
-
-MONGO_ADAPTER = "chatterbot.storage.MongoDatabaseAdapter"
-SQLITE_ADAPTER = "chatterbot.storage.SQLStorageAdapter"
-
-
-class ATRIChatBot:
-    bot = ChatBot(
-        "ATRI",
-        storage_adapter=MONGO_ADAPTER
-        if ChatterBot.mongo_database_uri
-        else SQLITE_ADAPTER,
-        logic_adapters=[
-            {
-                "import_path": "chatterbot.logic.BestMatch",
-                "default_response": ChatterBot.default_response,
-                "maximum_similarity_threshold": ChatterBot.maximum_similarity_threshold,
-            }
-        ],
-        database_uri=ChatterBot.mongo_database_uri,
-        read_only=True,  # 只能通过 learn 函数学习
-    )
-    list_trainer = ListTrainer(bot)
-    session_text_dict = dict()
-
-    @staticmethod
-    def learn_from_corpus():
-        trainer = ChatterBotCorpusTrainer(ATRIChatBot.bot)
-        # 从 corpus 的中文语料库学习,yaml 包太新的话需要把 corpus.py 的 yaml.load() 改成 yaml.full_load()
-        # 可以尝试用 https://github.com/hbwzhsh/chinese_chatbot_corpus 里面的语料进行训练
-        trainer.train("chatterbot.corpus.chinese")
-
-    @staticmethod
-    def learn(session_id: str, text: str):
-        # 查找上一条消息并训练模型
-        last_text = ATRIChatBot.session_text_dict.get(session_id)
-        if last_text:
-            ATRIChatBot.list_trainer.train([last_text, text])  # 问(可多个)  # 答
-        # 更新最后一条消息
-        ATRIChatBot.session_text_dict[session_id] = text
-
-    @staticmethod
-    async def get_response(text: str) -> str:
-        response = ATRIChatBot.bot.get_response(text)
-        log.info(f"人工智障回复:{text}  ->  {response.text}")
-        return response.text