Metadata-Version: 2.1
Name: ConversationAgent
Version: 0.2.1
Summary: ConversationAgent
Home-page: UNKNOWN
Author: Theta
License: MIT
Description: ## 說明
        不需資料庫之對話腳本代理。
        
        - 透過"ConversationAgent.LibStage.gen_agent"方法來建置機器人
        - 透過"ConversationAgent.to_bot"方式與機器人溝通
            - 該方法需要三個參數
                - agent代理物件: gen_agent 產生
                - text: 使用者輸入內容，字串內容
                - data: 過場資訊，預設使用`{}`空字典，第二次與之後溝通應該戴上 `to_bot` 回傳的資料。
            - 該方法會回傳機器人回應與過場資訊，下次溝通保留該過場資訊在進行溝通。
            
        ## Quick start
        ```
        from ConversationAgent.LibStage import gen_agent
        import ConversationAgent
        
        bot = {
            "__MAIN_STAGES__": [
                {
                    "stage_type": "__QA_STAGE__",
                    "qa_threshold": 1,
                    "says": {
                        "sys_welcome": "歡迎句",
                        "sys_refuse": "拒絕句",
                        "sys_complete": "完成句"
                    },
                    "corpus": {
                        "早安": "1",
                        "午安": "2",
                        "晚安": "3"
                    },
                    "__SAVED_NAME__": {
                        "__QA_RESPOND__": "QA_r1",
                        "__QA_RESPOND_THRESHOLD__": "QA_th",
                        "__QA_RESPOND_QUESTION__": "QA_q1",
                        "__QA_RESPOND_SCORE__": "QA_s1",
                        "__RUNNING_CORPUS__": "QA_c1",
                    },
                    "DISSABLE_WELCOME": False
                }
            ]
        }
        print(f"\n" * 5)
        
        agent = gen_agent(bot)
        data = {}
        reply_text, data = ConversationAgent.to_bot(agent, "哈囉", data)
        print(f"reply_text: {reply_text}， ")
        reply_text, data = ConversationAgent.to_bot(agent, "哈囉", data)
        print(f"reply_text: {reply_text}， ")
        reply_text, data = ConversationAgent.to_bot(agent, "早安", data)
        print(f"reply_text: {reply_text}， ")
        ```
        
        ## Stage 種類
        ### RE_STAGE
        
        RE_STAGE 採用`stage_type`為`__RE_STAGE__`，是用於最基礎的對話階段，由兩個主要結構構成：
        1. says: 用來設定該階段的回應句，回應句有三種類型
           * 歡迎句: 第一次到該階段時，機器人會回應該句子。(可依需求關閉功能，`DISSABLE_WELCOME`設為`True`就關閉，預設為`False`。)
           * 拒絕句: 當沒有滿足抓取到所有`is_fits`部分所要求的變數時，機器人會回應該句子。
           * 完成句: 以上都完成時，機器人會回應該句子。(可透過`%%`包裹變數名稱，並以`空格`前後相隔後，調用該變數。)
        
        2. is_fits: 透過`正規表達式(regular expression)`從使用者的輸入句子來抓取變數，該變數會儲存起來提供給`完成句`和 `SWITCH_STAGE`使用。
        
        
        ```
        {
            "stage_type": "__RE_STAGE__",
            "says": {
                "sys_welcome": "歡迎句",
                "sys_refuse": "拒絕句",
                "sys_complete": "完成句 %%YOUSAYS%% " 
            },
            "is_fits": [
                [".*", "YOUSAYS"]
            ],
            "DISSABLE_WELCOME": False
        }
        ```
        
        ### SWITCH_STAGE
        
        SWITCH_STAGE 採用`stage_type`為`__LIB_SWITCH_STAGE__`，用於在`Agent`不同路線切換，主要結構是`stages_filter`。 stages_filter用來設定切換路線的條件，用`[]`可包含帶多種條件多路線，每一條件單位由`變數名稱`、`限定數值`和 `切換路線`三部分組成。
        
        以下說明主要四種設置方式:
        * 無條件設定:
            ```
            [
                ["*",True,"_新路線1_"]
            ]
            ```
        * 單一條件設定:
            ```
            [
                ["_VAR_","VALUE1","_新路線1_"],
                ["_VAR_","VALUE2","_新路線2_"]
            ]
            ```
        * 多條件設定:
            ```
            [
                [["_VAR1_","_VAR2_"],["VALUE1","VALUE2"],"_新路線1_"],
                [["_VAR1_","_VAR2_"],["VALUE3","VALUE4"],"_新路線2_"],
            ]
            ```
        * 混合條件設定:
            ```
            [
                ["_VAR1_","VALUE1","_新路線1_"],
                [["_VAR1_","_VAR2_"],["VALUE3","VALUE4"],"_新路線2_"],
                ["*",True,"_新路線3_"]
            ]
            ```
        
        **儲存變數方式是透過`RE_STAGE`的 `is_fits`來執行。
        
        範例：
        ```
        {
            "stage_type": "__LIB_SWITCH_STAGE__",
            "stages_filter": [
                ["VAR","我想要的數值","_成功路線_"],,
                ["*",True,"_失敗路線_"]
            ]
        
        }
        ```
        
        ### QA_STAGE
        QA_STAGE 採用`stage_type`為`__QA_STAGE__`，是通過`相似度`來決定回應的一種階段，主要有三個部分的組成。
        1. says: 用來設定該階段的回應句，回應句有三種類型
           * 歡迎句: 第一次到該階段時，機器人會回應該句子。(可依需求關閉功能，`DISSABLE_WELCOME`設為`True`就關閉，預設為`False`。)
           * 拒絕句: 當相似分數低於`qa_threshold`時，機器人會回應該句子。
           * 完成句: 以上都完成時，機器人會回應該句子。(可透過`%%`包裹變數名稱，並以`空格`前後相隔後，調用該變數。)
        
        2. corpus: 使用者的輸入會與該字典的所有`key`進行比對，並儲存相關結果，相關結果包含：
            * `__QA_RESPOND_QUESTION__`: 相似值最高的 key
            * `__QA_RESPOND__`: 相似值最高的 key 對應之 value
            * `__QA_RESPOND_SCORE__`: 相似值最高的數值
            * `__RUNNING_CORPUS__`: 該次測試時使用的 corpus
            * `__QA_RESPOND_THRESHOLD__`: 該次測試使用的 threshold
            
        3. `__SAVED_NAME__`: 設定儲存之變數的名稱，方便使用。
        
        ```
         {
            "stage_type": "__QA_STAGE__",
            "qa_threshold": 1,
            "says": {
                "sys_welcome": "歡迎句",
                "sys_refuse": "拒絕句",
                "sys_complete": "完成句"
            },
            "corpus": {
                "早安": "1",
                "午安": "2",
                "晚安": "3"
            },
            "__SAVED_NAME__": {
                QAStage.__QA_RESPOND__: "QA_r1",
                QAStage.__QA_RESPOND_THRESHOLD__: "QA_th",
                QAStage.__QA_RESPOND_QUESTION__: "QA_q1",
                QAStage.__QA_RESPOND_SCORE__: "QA_s1",
                QAStage.__RUNNING_CORPUS__: "QA_c1",
            },
            "DISSABLE_WELCOME": False
        }
        ```
        
        
        
        ## Example
        ### 購票系統範例 
        ```
        from ConversationAgent.LibStage import gen_multi_agent, QAStage
        import ConversationAgent
        bot_json = {
          "__MAIN_STAGES__": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "請問是要做哪種票種呢？",
                "sys_reply_q2": "請說『月票』或是『單程票』",
                "sys_reply_complete": "好的，將開始訂購 %%set_level%% "
              },
              "is_fits": [
                [
                  "(月票|1280|長期票|定期票)+",
                  "set_level"
                ],
                [
                  "(單程票|單程|一次)+",
                  "set_level"
                ]
              ]
            },
            {
              "stage_type": "Switch",
              "stages_filter": [
                [
                  "set_level",
                  "月票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "1280",
                  "_月票_"
                ],
                [
                  "set_level",
                  "長期票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "定期票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "單程票",
                  "_單程票_"
                ],
                [
                  "set_level",
                  "單程",
                  "_單程票_"
                ],
                [
                  "set_level",
                  "一次",
                  "_單程票_"
                ]
              ]
            }
          ],
          "_月票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "月票的價格為 1280元，是否確認？",
                "sys_reply_q2": "月票的價格為 1280元，是否確認？請回答『是』或『否』",
                "sys_reply_complete": "好的，確認您使用 %%set_level%% 車廂的意願為 『 %%user_status%% 』，\n            感謝您的使用。\n        "
              },
              "is_fits": [
                [
                  "(是|好的|好|沒問題)+$",
                  "user_status"
                ],
                [
                  "(否|不|不行|不要|不好)+$",
                  "user_status"
                ]
              ]
            }
          ],
          "_單程票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "",
                "sys_reply_q2": "",
                "sys_reply_complete": "如果要訂購單程票，請使用票卷機，感謝您的使用。\n        "
              },
              "is_fits": [],
              "__DISSABLE_Q1__": True
            }
          ]
        }
        data = {}
        agent = gen_multi_agent(bot_json)
        
        #
        text = "hi"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        
        #
        text = "月票"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        
        #
        text = "好"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        ```
        
        ### 購票+問答系統範例 
        ```
        from ConversationAgent.LibStage import gen_multi_agent, QAStage
        import ConversationAgent
        bot_json = {
          "__MAIN_STAGES__": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "哈囉請問要做什麼？ 目前提供『問答』和『訂票』服務",
                "sys_reply_q2": "目前只提供『問答』和『訂票』服務喔",
                "sys_reply_complete": "好的，將開始 『 %%selected_service%% 』 "
              },
              "is_fits": [
                [
                  "(問答|問題|詢問)+",
                  "selected_service"
                ],
                [
                  "(訂票|票價|買票)+",
                  "selected_service"
                ]
              ]
            },
            {
              "stage_type": "Switch",
              "stages_filter": [
                [
                  "selected_service",
                  "訂票",
                  "_訂票_"
                ],
                [
                  "selected_service",
                  "買票",
                  "_訂票_"
                ],
                [
                  "selected_service",
                  "票價",
                  "_訂票_"
                ],
                [
                  "selected_service",
                  "問答",
                  "_問答_"
                ],
                [
                  "selected_service",
                  "問題",
                  "_問答_"
                ],
                [
                  "selected_service",
                  "詢問",
                  "_問答_"
                ]
              ]
            }
          ],
          "_問答_": [
            {
              "stage_type": "__QA_STAGE__",
              "corpus": {
                "廁所在哪裡": "這裡沒有廁所",
                "詢問處在哪裡": "這裡沒有詢問處",
                "診所在哪裡": "這裡沒有診所",
              },
              "question": {
                "sys_reply_q1": "請問有什麼問題呢？",
                "sys_reply_q2": "",
                "sys_reply_complete": "我有 %%__QA_RESPOND_SCORE__%% 的信心覺得您要問：<br> \n        %%__QA_RESPOND_QUESTION__%% <br> \n        答案是 %%__QA_RESPOND__%% "
              },
              "is_fits": []
            }
          ],
          "_訂票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "請問是要做哪種票種呢？",
                "sys_reply_q2": "請說『月票』或是『單程票』",
                "sys_reply_complete": "好的，將開始訂購 %%set_level%% "
              },
              "is_fits": [
                [
                  "(月票|1280|長期票|定期票)+",
                  "set_level"
                ],
                [
                  "(單程票|單程|一次)+",
                  "set_level"
                ]
              ]
            },
            {
              "stage_type": "Switch",
              "stages_filter": [
                [
                  "set_level",
                  "月票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "1280",
                  "_月票_"
                ],
                [
                  "set_level",
                  "長期票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "定期票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "單程票",
                  "_單程票_"
                ],
                [
                  "set_level",
                  "單程",
                  "_單程票_"
                ],
                [
                  "set_level",
                  "一次",
                  "_單程票_"
                ]
              ]
            }
          ],
          "_月票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "月票的價格為 1280元，是否確認？",
                "sys_reply_q2": "月票的價格為 1280元，是否確認？請回答『是』或『否』",
                "sys_reply_complete": "好的，確認您使用 %%set_level%% 車廂的意願為 『 %%user_status%% 』，\n            感謝您的使用。\n        "
              },
              "is_fits": [
                [
                  "(是|好的|好|沒問題)+$",
                  "user_status"
                ],
                [
                  "(否|不|不行|不要|不好)+$",
                  "user_status"
                ]
              ]
            }
          ],
          "_單程票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "",
                "sys_reply_q2": "",
                "sys_reply_complete": "如果要訂購單程票，請使用票卷機，感謝您的使用。\n        "
              },
              "is_fits": [],
              "__DISSABLE_Q1__": True
            }
          ]
        }
        data = {}
        agent = gen_multi_agent(bot_json)
        
        #
        text = "hi"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        
        #
        text = "我要月票"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        
        #
        text = "好"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        ```
        
        ### 如何客製化類別：以購票+問答系統為例子 
        ```
        from ConversationAgent.LibStage import __LIB_STAGES__
        from ConversationAgent.LibStage import QAStage
        import requests
        
        
        """
        ##########
        __NEW QAWorkerSTAGE__
        ##########
        """
        __NEW_QUESTIONANSWER__ = "NEW_QUESTIONANSWER"
        class QAWorkerSTAGE(QAStage):
            def __init__(self,data):
                super(QAWorkerSTAGE, self).__init__(data)
                self.similar_method = data.get(self.__SIMILAR_METHOD__, "worker_api")
                self.__NLPCORESERVER__ = "http://52.147.71.0:8000"
        
            def __request_similar_api__(self,text,corpus):
                res = requests.post(url=f"{self.__NLPCORESERVER__}/jobs/{self.similar_method}", json={
                    "sentence": [
                        text
                    ],
                    "corpus": corpus})
                return res.json()
        
        # 增加自訂義的類別
        __LIB_STAGES__[__NEW_QUESTIONANSWER__] = QAWorkerSTAGE
        
        """
        ##########
        Bot
        ##########
        """        
        bot_json = {
          "__MAIN_STAGES__": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "哈囉請問要做什麼？ 目前提供『問答』和『訂票』服務",
                "sys_reply_q2": "目前只提供『問答』和『訂票』服務喔",
                "sys_reply_complete": "好的，將開始 『 %%selected_service%% 』 "
              },
              "is_fits": [
                [
                  "(問答|問題|詢問)+",
                  "selected_service"
                ],
                [
                  "(訂票|票價|買票)+",
                  "selected_service"
                ]
              ]
            },
            {
              "stage_type": "Switch",
              "stages_filter": [
                [
                  "selected_service",
                  "訂票",
                  "_訂票_"
                ],
                [
                  "selected_service",
                  "買票",
                  "_訂票_"
                ],
                [
                  "selected_service",
                  "票價",
                  "_訂票_"
                ],
                [
                  "selected_service",
                  "問答",
                  "_問答_"
                ],
                [
                  "selected_service",
                  "問題",
                  "_問答_"
                ],
                [
                  "selected_service",
                  "詢問",
                  "_問答_"
                ]
              ]
            }
          ],
          "_問答_": [
            {
              "stage_type": __NEW_QUESTIONANSWER__,
              "corpus": {
                "廁所在哪裡": "這裡沒有廁所",
                "詢問處在哪裡": "這裡沒有詢問處",
                "診所在哪裡": "這裡沒有診所",
              },
              "question": {
                "sys_reply_q1": "請問有什麼問題呢？",
                "sys_reply_q2": "",
                "sys_reply_complete": "我有 %%__QA_RESPOND_SCORE__%% 的信心覺得您要問：<br> \n        %%__QA_RESPOND_QUESTION__%% <br> \n        答案是 %%__QA_RESPOND__%% "
              },
              "is_fits": []
            }
          ],
          "_訂票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "請問是要做哪種票種呢？",
                "sys_reply_q2": "請說『月票』或是『單程票』",
                "sys_reply_complete": "好的，將開始訂購 %%set_level%% "
              },
              "is_fits": [
                [
                  "(月票|1280|長期票|定期票)+",
                  "set_level"
                ],
                [
                  "(單程票|單程|一次)+",
                  "set_level"
                ]
              ]
            },
            {
              "stage_type": "Switch",
              "stages_filter": [
                [
                  "set_level",
                  "月票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "1280",
                  "_月票_"
                ],
                [
                  "set_level",
                  "長期票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "定期票",
                  "_月票_"
                ],
                [
                  "set_level",
                  "單程票",
                  "_單程票_"
                ],
                [
                  "set_level",
                  "單程",
                  "_單程票_"
                ],
                [
                  "set_level",
                  "一次",
                  "_單程票_"
                ]
              ]
            }
          ],
          "_月票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "月票的價格為 1280元，是否確認？",
                "sys_reply_q2": "月票的價格為 1280元，是否確認？請回答『是』或『否』",
                "sys_reply_complete": "好的，確認您使用 %%set_level%% 車廂的意願為 『 %%user_status%% 』，\n            感謝您的使用。\n        "
              },
              "is_fits": [
                [
                  "(是|好的|好|沒問題)+$",
                  "user_status"
                ],
                [
                  "(否|不|不行|不要|不好)+$",
                  "user_status"
                ]
              ]
            }
          ],
          "_單程票_": [
            {
              "stage_type": "__RE_STAGE__",
              "question": {
                "sys_reply_q1": "",
                "sys_reply_q2": "",
                "sys_reply_complete": "如果要訂購單程票，請使用票卷機，感謝您的使用。\n        "
              },
              "is_fits": [],
              "__DISSABLE_Q1__": True
            }
          ]
        }
        data = {}
        agent = gen_multi_agent(bot_json)
        
        
        
        #
        text = "hi"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        
        #
        text = "我有點問題"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        
        #
        text = "附近有廁所嗎"
        reply_text, data = ConversationAgent.mock_client_once(agent, text, data)
        print(f"data: {data}")
        print(f"reply_text: {reply_text}")
        ```
        
        ## ToDo
        
        * Switch除了等號以外的方法
        * DISSABLE_WELCOME測試與勘誤名詞
        * Not Found Path時回應一個錯誤用的stage
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