{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {
                "collapsed": false
            },
            "source": [
                "![Logo 1](https://git.wmi.amu.edu.pl/AITech/Szablon/raw/branch/master/Logotyp_AITech1.jpg)\n",
                "<div class=\"alert alert-block alert-info\">\n",
                "<h1> Systemy Dialogowe </h1>\n",
                "<h2> 9. <i>Zarządzanie dialogiem z wykorzystaniem reguł</i>  [laboratoria]</h2> \n",
                "<h3> Marek Kubis (2021)</h3>\n",
                "</div>\n",
                "\n",
                "![Logo 2](https://git.wmi.amu.edu.pl/AITech/Szablon/raw/branch/master/Logotyp_AITech2.jpg)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Zarządzanie dialogiem z wykorzystaniem reguł\n",
                "============================================\n",
                "\n",
                "Agent dialogowy wykorzystuje do zarządzanie dialogiem dwa moduły:\n",
                "\n",
                "  - monitor stanu dialogu (dialogue state tracker, DST) — moduł odpowiedzialny za śledzenie stanu dialogu.\n",
                "\n",
                "  - taktykę prowadzenia dialogu (dialogue policy) — moduł, który na podstawie stanu dialogu\n",
                "    podejmuje decyzję o tym jaką akcję (akt systemu) agent ma podjąć w kolejnej turze.\n",
                "\n",
                "Oba moduły mogą być realizowane zarówno z wykorzystaniem reguł jak i uczenia maszynowego.\n",
                "Mogą one zostać również połączone w pojedynczy moduł zwany wówczas *menedżerem dialogu*.\n",
                "\n",
                "Przykład\n",
                "--------\n",
                "\n",
                "Zaimplementujemy regułowe moduły monitora stanu dialogu oraz taktyki dialogowej a następnie\n",
                "osadzimy je w środowisku *[ConvLab-2](https://github.com/thu-coai/ConvLab-2)*,\n",
                "które służy do ewaluacji systemów dialogowych.\n",
                "\n",
                "**Uwaga:** Niektóre moduły środowiska *ConvLab-2* nie są zgodne z najnowszymi wersjami Pythona,\n",
                "dlatego przed uruchomieniem poniższych przykładów należy się upewnić, że mają Państwo interpreter\n",
                "Pythona w wersji 3.7. W przypadku nowszych wersji Ubuntu Pythona 3.7 można zainstalować z\n",
                "repozytorium `deadsnakes`, wykonując polecenia przedstawione poniżej.\n",
                "\n",
                "```\n",
                "sudo add-apt-repository ppa:deadsnakes/ppa\n",
                "sudo apt update\n",
                "sudo apt install python3.7 python3.7-dev python3.7-venv\n",
                "```\n",
                "\n",
                "W przypadku innych systemów można skorzystać np. z narzędzia [pyenv](https://github.com/pyenv/pyenv) lub środowiska [conda](https://conda.io).\n",
                "\n",
                "Ze względu na to, że *ConvLab-2* ma wiele zależności zachęcam również do skorzystania ze środowiska\n",
                "wirtualnego `venv`, w którym moduły zależne mogą zostać zainstalowane.\n",
                "W tym celu należy wykonać następujące polecenia\n",
                "\n",
                "```\n",
                "python3.7 -m venv convenv                     # utworzenie nowego środowiska o nazwie convenv\n",
                "source convenv/bin/activate                   # aktywacja środowiska w bieżącej powłoce\n",
                "pip install --ignore-installed jupyter        # instalacja jupytera w środowisku convenv\n",
                "```\n",
                "\n",
                "Po skonfigurowaniu środowiska można przystąpić do instalacji *ConvLab-2*, korzystając z\n",
                "następujących poleceń\n",
                "\n",
                "```\n",
                "mkdir -p l08\n",
                "cd l08\n",
                "git clone https://github.com/thu-coai/ConvLab-2.git\n",
                "cd ConvLab-2\n",
                "pip install -e .\n",
                "python -m spacy download en_core_web_sm\n",
                "cd ../..\n",
                "```\n",
                "\n",
                "Po zakończeniu instalacji należy ponownie uruchomić notatnik w powłoce, w której aktywne jest\n",
                "środowisko wirtualne *convenv*.\n",
                "\n",
                "```\n",
                "jupyter notebook 08-zarzadzanie-dialogiem-reguly.ipynb\n",
                "```\n",
                "\n",
                "Działanie zaimplementowanych modułów zilustrujemy, korzystając ze zbioru danych\n",
                "[MultiWOZ](https://github.com/budzianowski/multiwoz) (Budzianowski i in., 2018), który zawiera\n",
                "wypowiedzi dotyczące m.in. rezerwacji pokoi hotelowych, zamawiania biletów kolejowych oraz\n",
                "rezerwacji stolików w restauracji.\n",
                "\n",
                "### Monitor Stanu Dialogu\n",
                "\n",
                "Do reprezentowania stanu dialogu użyjemy struktury danych wykorzystywanej w *ConvLab-2*."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "{'user_action': [],\n",
                            " 'system_action': [],\n",
                            " 'belief_state': {'cinema': {'book': {'title': '',\n",
                            "    'date': '',\n",
                            "    'time': '',\n",
                            "    'quantity': '',\n",
                            "    'seats': '',\n",
                            "    'area': '',\n",
                            "    'interval': ''},\n",
                            "   'semi': {'goal': ''}}},\n",
                            " 'request_state': {},\n",
                            " 'terminated': False,\n",
                            " 'history': []}"
                        ]
                    },
                    "execution_count": 3,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "# from convlab2.util.multiwoz.state import default_state\n",
                "from utils.state import default_state\n",
                "default_state()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Metoda `update` naszego monitora stanu dialogu będzie przyjmować akty użytkownika i odpowiednio\n",
                "modyfikować stan dialogu.\n",
                "W przypadku aktów typu `inform` wartości slotów zostaną zapamiętane w słownikach odpowiadających\n",
                "poszczególnym dziedzinom pod kluczem `belief_state`.\n",
                "W przypadku aktów typu `request` sloty, o które pyta użytkownik zostaną zapisane pod kluczem\n",
                "`request_state`.\n"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 34,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "\"\\nclass SimpleRuleDST(DST):\\n    def __init__(self):\\n        DST.__init__(self)\\n        self.state = default_state()\\n        self.value_dict = json.load(open('l08/ConvLab-2/data/multiwoz/value_dict.json'))\\n\\n    def update(self, user_act=None):\\n        for intent, domain, slot, value in user_act:\\n            domain = domain.lower()\\n            intent = intent.lower()\\n\\n            if domain in ['unk', 'general', 'booking']:\\n                continue\\n\\n            if intent == 'inform':\\n                k = REF_SYS_DA[domain.capitalize()].get(slot, slot)\\n\\n                if k is None:\\n                    continue\\n\\n                domain_dic = self.state['belief_state'][domain]\\n\\n                if k in domain_dic['semi']:\\n                    nvalue = normalize_value(self.value_dict, domain, k, value)\\n                    self.state['belief_state'][domain]['semi'][k] = nvalue\\n                elif k in domain_dic['book']:\\n                    self.state['belief_state'][domain]['book'][k] = value\\n                elif k.lower() in domain_dic['book']:\\n                    self.state['belief_state'][domain]['book'][k.lower()] = value\\n            elif intent == 'request':\\n                k = REF_SYS_DA[domain.capitalize()].get(slot, slot)\\n\\n                if domain not in self.state['request_state']:\\n                    self.state['request_state'][domain] = {}\\n                if k not in self.state['request_state'][domain]:\\n                    self.state['request_state'][domain][k] = 0\\n\\n        return self.state\\n\\n    def init_session(self):\\n        self.state = default_state()\\n\""
                        ]
                    },
                    "execution_count": 34,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "import json\n",
                "import os\n",
                "from convlab2.dst.dst import DST\n",
                "from convlab2.dst.rule.multiwoz.dst_util import normalize_value\n",
                "from convlab2.util.multiwoz.multiwoz_slot_trans import REF_SYS_DA\n",
                "\n",
                "class SimpleRuleDST(DST):\n",
                "    def __init__(self):\n",
                "        DST.__init__(self)\n",
                "        self.state = default_state()\n",
                "        self.value_dict = json.load(open('utils/value_dict.json'))\n",
                "\n",
                "    def update(self, user_act=None):\n",
                "        for intent, domain, slot, value in user_act:\n",
                "            domain = domain.lower()\n",
                "            intent = intent.lower()\n",
                "            value = value.lower()\n",
                "\n",
                "            # if domain in ['unk', 'cinema']:\n",
                "            #     continue\n",
                "            k = slot\n",
                "\n",
                "            if intent == 'inform':\n",
                "                # k = REF_SYS_DA[domain.capitalize()].get(slot, slot)\n",
                "                # if k is None:\n",
                "                #     continue\n",
                "\n",
                "                domain_dic = self.state['belief_state'][domain]\n",
                "\n",
                "                if k in domain_dic['semi']:\n",
                "                    # nvalue = normalize_value(self.value_dict, domain, k, value)\n",
                "                    self.state['belief_state'][domain]['semi'][k] = value\n",
                "                elif k in domain_dic['book']:\n",
                "                    self.state['belief_state'][domain]['book'][k] = value\n",
                "                elif k.lower() in domain_dic['book']:\n",
                "                    self.state['belief_state'][domain]['book'][k.lower()] = value\n",
                "            elif intent == 'request':\n",
                "                # k = REF_SYS_DA[domain.capitalize()].get(slot, slot)\n",
                "\n",
                "                if domain not in self.state['request_state']:\n",
                "                    self.state['request_state'][domain] = {}\n",
                "                if k not in self.state['request_state'][domain]:\n",
                "                    self.state['request_state'][domain][k] = 0\n",
                "\n",
                "        return self.state\n",
                "\n",
                "    def init_session(self):\n",
                "        self.state = default_state()\n",
                "\n",
                "'''\n",
                "class SimpleRuleDST(DST):\n",
                "    def __init__(self):\n",
                "        DST.__init__(self)\n",
                "        self.state = default_state()\n",
                "        self.value_dict = json.load(open('l08/ConvLab-2/data/multiwoz/value_dict.json'))\n",
                "\n",
                "    def update(self, user_act=None):\n",
                "        for intent, domain, slot, value in user_act:\n",
                "            domain = domain.lower()\n",
                "            intent = intent.lower()\n",
                "\n",
                "            if domain in ['unk', 'general', 'booking']:\n",
                "                continue\n",
                "\n",
                "            if intent == 'inform':\n",
                "                k = REF_SYS_DA[domain.capitalize()].get(slot, slot)\n",
                "\n",
                "                if k is None:\n",
                "                    continue\n",
                "\n",
                "                domain_dic = self.state['belief_state'][domain]\n",
                "\n",
                "                if k in domain_dic['semi']:\n",
                "                    nvalue = normalize_value(self.value_dict, domain, k, value)\n",
                "                    self.state['belief_state'][domain]['semi'][k] = nvalue\n",
                "                elif k in domain_dic['book']:\n",
                "                    self.state['belief_state'][domain]['book'][k] = value\n",
                "                elif k.lower() in domain_dic['book']:\n",
                "                    self.state['belief_state'][domain]['book'][k.lower()] = value\n",
                "            elif intent == 'request':\n",
                "                k = REF_SYS_DA[domain.capitalize()].get(slot, slot)\n",
                "\n",
                "                if domain not in self.state['request_state']:\n",
                "                    self.state['request_state'][domain] = {}\n",
                "                if k not in self.state['request_state'][domain]:\n",
                "                    self.state['request_state'][domain][k] = 0\n",
                "\n",
                "        return self.state\n",
                "\n",
                "    def init_session(self):\n",
                "        self.state = default_state()\n",
                "'''\n"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "W definicji metody `update` zakładamy, że akty dialogowe przekazywane do monitora stanu dialogu z\n",
                "modułu NLU są czteroelementowymi listami złożonymi z:\n",
                "\n",
                " - nazwy aktu użytkownika,\n",
                " - nazwy dziedziny, której dotyczy wypowiedź,\n",
                " - nazwy slotu,\n",
                " - wartości slotu.\n",
                "\n",
                "Zobaczmy na kilku prostych przykładach jak stan dialogu zmienia się pod wpływem przekazanych aktów\n",
                "użytkownika."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 35,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "{'user_action': [],\n",
                            " 'system_action': [],\n",
                            " 'belief_state': {'cinema': {'book': {'title': '',\n",
                            "    'date': '',\n",
                            "    'time': '',\n",
                            "    'quantity': '',\n",
                            "    'seats': '',\n",
                            "    'area': '',\n",
                            "    'interval': ''},\n",
                            "   'semi': {'goal': ''}}},\n",
                            " 'request_state': {},\n",
                            " 'terminated': False,\n",
                            " 'history': []}"
                        ]
                    },
                    "execution_count": 35,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "dst = SimpleRuleDST()\n",
                "dst.state"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 36,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "{'book': {'title': 'batman',\n",
                            "  'date': '',\n",
                            "  'time': '15:00',\n",
                            "  'quantity': '',\n",
                            "  'seats': '',\n",
                            "  'area': '',\n",
                            "  'interval': ''},\n",
                            " 'semi': {'goal': ''}}"
                        ]
                    },
                    "execution_count": 36,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "dst.update([['Inform', 'Cinema', 'time', '15:00'], ['Inform', 'Cinema', 'title', 'Batman']])\n",
                "dst.state['belief_state']['cinema']"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 37,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "{'book': {'title': 'batman',\n",
                            "  'date': '',\n",
                            "  'time': '15:00',\n",
                            "  'quantity': '',\n",
                            "  'seats': '',\n",
                            "  'area': 'na górze na środku',\n",
                            "  'interval': ''},\n",
                            " 'semi': {'goal': ''}}"
                        ]
                    },
                    "execution_count": 37,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "dst.update([['Inform', 'Cinema', 'area', 'na górze na środku']])\n",
                "dst.state['belief_state']['cinema']"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 38,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "{'cinema': {'date': 0}}"
                        ]
                    },
                    "execution_count": 38,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "dst.update([['Request', 'Cinema', 'date', '?']])\n",
                "dst.state['request_state']"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "dst.update([['Inform', 'Hotel', 'Day', 'tuesday'], ['Inform', 'Hotel', 'People', '2'], ['Inform', 'Hotel', 'Stay', '4']])\n",
                "dst.state['belief_state']['hotel']"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 39,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "{'user_action': [],\n",
                            " 'system_action': [],\n",
                            " 'belief_state': {'cinema': {'book': {'title': 'batman',\n",
                            "    'date': '',\n",
                            "    'time': '15:00',\n",
                            "    'quantity': '',\n",
                            "    'seats': '',\n",
                            "    'area': 'na górze na środku',\n",
                            "    'interval': ''},\n",
                            "   'semi': {'goal': ''}}},\n",
                            " 'request_state': {'cinema': {'date': 0}},\n",
                            " 'terminated': False,\n",
                            " 'history': []}"
                        ]
                    },
                    "execution_count": 39,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "dst.state"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Taktyka Prowadzenia Dialogu\n",
                "\n",
                "Prosta taktyka prowadzenia dialogu dla systemu rezerwacji pokoi hotelowych może składać się z następujących reguł:\n",
                "\n",
                " 1. Jeżeli użytkownik przekazał w ostatniej turze akt typu `Request`, to udziel odpowiedzi na jego\n",
                "    pytanie.\n",
                "\n",
                " 2. Jeżeli użytkownik przekazał w ostatniej turze akt typu `Inform`, to zaproponuj mu hotel\n",
                "    spełniający zdefiniowane przez niego kryteria.\n",
                "\n",
                " 3. Jeżeli użytkownik przekazał w ostatniej turze akt typu `Inform` zawierający szczegóły\n",
                "    rezerwacji, to zarezerwuj pokój.\n",
                "\n",
                "Metoda `predict` taktyki `SimpleRulePolicy` realizuje reguły przedstawione powyżej."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "from collections import defaultdict\n",
                "import copy\n",
                "import json\n",
                "from copy import deepcopy\n",
                "\n",
                "from convlab2.policy.policy import Policy\n",
                "from convlab2.util.multiwoz.dbquery import Database\n",
                "from convlab2.util.multiwoz.multiwoz_slot_trans import REF_SYS_DA, REF_USR_DA\n",
                "\n",
                "\n",
                "class SimpleRulePolicy(Policy):\n",
                "    def __init__(self):\n",
                "        Policy.__init__(self)\n",
                "        self.db = Database()\n",
                "\n",
                "    def predict(self, state):\n",
                "        self.results = []\n",
                "        system_action = defaultdict(list)\n",
                "        user_action = defaultdict(list)\n",
                "\n",
                "        for intent, domain, slot, value in state['user_action']:\n",
                "            user_action[(domain, intent)].append((slot, value))\n",
                "\n",
                "        for user_act in user_action:\n",
                "            self.update_system_action(user_act, user_action, state, system_action)\n",
                "\n",
                "        # Reguła 3\n",
                "        if any(True for slots in user_action.values() for (slot, _) in slots if slot in ['Stay', 'Day', 'People']):\n",
                "            if self.results:\n",
                "                system_action = {('Booking', 'Book'): [[\"Ref\", self.results[0].get('Ref', 'N/A')]]}\n",
                "\n",
                "        system_acts = [[intent, domain, slot, value] for (domain, intent), slots in system_action.items() for slot, value in slots]\n",
                "        state['system_action'] = system_acts\n",
                "        return system_acts\n",
                "\n",
                "    def update_system_action(self, user_act, user_action, state, system_action):\n",
                "        domain, intent = user_act\n",
                "        constraints = [(slot, value) for slot, value in state['belief_state'][domain.lower()]['semi'].items() if value != '']\n",
                "        self.results = deepcopy(self.db.query(domain.lower(), constraints))\n",
                "\n",
                "        # Reguła 1\n",
                "        if intent == 'Request':\n",
                "            if len(self.results) == 0:\n",
                "                system_action[(domain, 'NoOffer')] = []\n",
                "            else:\n",
                "                for slot in user_action[user_act]:\n",
                "                    kb_slot_name = REF_SYS_DA[domain].get(slot[0], slot[0])\n",
                "\n",
                "                    if kb_slot_name in self.results[0]:\n",
                "                        system_action[(domain, 'Inform')].append([slot[0], self.results[0].get(kb_slot_name, 'unknown')])\n",
                "\n",
                "        # Reguła 2\n",
                "        elif intent == 'Inform':\n",
                "            if len(self.results) == 0:\n",
                "                system_action[(domain, 'NoOffer')] = []\n",
                "            else:\n",
                "                system_action[(domain, 'Inform')].append(['Choice', str(len(self.results))])\n",
                "                choice = self.results[0]\n",
                "\n",
                "                if domain in [\"Hotel\", \"Attraction\", \"Police\", \"Restaurant\"]:\n",
                "                    system_action[(domain, 'Recommend')].append(['Name', choice['name']])"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Podobnie jak w przypadku aktów użytkownika akty systemowe przekazywane do modułu NLG są czteroelementowymi listami złożonymi z:\n",
                "\n",
                " - nazwy aktu systemowe,\n",
                " - nazwy dziedziny, której dotyczy wypowiedź,\n",
                " - nazwy slotu,\n",
                " - wartości slotu.\n",
                "\n",
                "Sprawdźmy jakie akty systemowe zwraca taktyka `SimpleRulePolicy` w odpowiedzi na zmieniający się stan dialogu."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "from convlab2.dialog_agent import PipelineAgent\n",
                "dst.init_session()\n",
                "policy = SimpleRulePolicy()\n",
                "agent = PipelineAgent(nlu=None, dst=dst, policy=policy, nlg=None, name='sys')"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response([['Inform', 'Hotel', 'Price', 'cheap'], ['Inform', 'Hotel', 'Parking', 'yes']])"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response([['Inform', 'Hotel', 'Area', 'north']])"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response([['Request', 'Hotel', 'Area', '?']])"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response([['Inform', 'Hotel', 'Day', 'tuesday'], ['Inform', 'Hotel', 'People', '2'], ['Inform', 'Hotel', 'Stay', '4']])"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "### Testy End-to-End\n",
                "\n",
                "Na koniec przeprowadźmy dialog łącząc w potok nasze moduły\n",
                "z modułami NLU i NLG dostępnymi dla MultiWOZ w środowisku `ConvLab-2`."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "from convlab2.nlu.svm.multiwoz import SVMNLU\n",
                "from convlab2.nlg.template.multiwoz import TemplateNLG\n",
                "\n",
                "nlu = SVMNLU()\n",
                "nlg = TemplateNLG(is_user=False)\n",
                "agent = PipelineAgent(nlu=nlu, dst=dst, policy=policy, nlg=nlg, name='sys')"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response(\"I need a cheap hotel with free parking .\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response(\"Where it is located ?\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {
                "lines_to_next_cell": 0
            },
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response(\"I would prefer the hotel be in the north part of town .\")"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": null,
            "metadata": {},
            "outputs": [
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                },
                {
                    "ename": "",
                    "evalue": "",
                    "output_type": "error",
                    "traceback": [
                        "\u001b[1;31mRunning cells with 'Python 3.6.15 ('sysdial')' requires ipykernel package.\n",
                        "Run the following command to install 'ipykernel' into the Python environment. \n",
                        "Command: 'conda install -n sysdial ipykernel --update-deps --force-reinstall'"
                    ]
                }
            ],
            "source": [
                "agent.response(\"Yeah , could you book me a room for 2 people for 4 nights starting Tuesday ?\")"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Zauważmy, ze nasza prosta taktyka dialogowa zawiera wiele luk, do których należą m.in.:\n",
                "\n",
                " 1. Niezdolność do udzielenia odpowiedzi na przywitanie, prośbę o pomoc lub restart.\n",
                "\n",
                " 2. Brak reguł dopytujących użytkownika o szczegóły niezbędne do dokonania rezerwacji takie, jak długość pobytu czy liczba osób.\n",
                "\n",
                "Bardziej zaawansowane moduły zarządzania dialogiem zbudowane z wykorzystaniem reguł można znaleźć w\n",
                "środowisku `ConvLab-2`. Należą do nich m.in. monitor [RuleDST](https://github.com/thu-coai/ConvLab-2/blob/master/convlab2/dst/rule/multiwoz/dst.py) oraz taktyka [RuleBasedMultiwozBot](https://github.com/thu-coai/ConvLab-2/blob/master/convlab2/policy/rule/multiwoz/rule_based_multiwoz_bot.py).\n",
                "\n",
                "Zadania\n",
                "-------\n",
                " 1. Zaimplementować w projekcie monitor stanu dialogu.\n",
                "\n",
                " 2. Zaimplementować w projekcie taktykę prowadzenia dialogu.\n",
                "\n",
                "Termin: 24.05.2021, godz. 23:59.\n",
                "\n",
                "Literatura\n",
                "----------\n",
                " 1. Pawel Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, Milica Gasic, MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling. EMNLP 2018, pp. 5016-5026\n",
                " 2. Cathy Pearl, Basic principles for designing voice user interfaces, https://www.oreilly.com/content/basic-principles-for-designing-voice-user-interfaces/ data dostępu: 21 marca 2021\n",
                " 3. Cathy Pearl, Designing Voice User Interfaces, Excerpts from Chapter 5: Advanced Voice User Interface Design, https://www.uxmatters.com/mt/archives/2018/01/designing-voice-user-interfaces.php data dostępu: 21 marca 2021"
            ]
        }
    ],
    "metadata": {
        "author": "Marek Kubis",
        "email": "mkubis@amu.edu.pl",
        "interpreter": {
            "hash": "91e2b0d1baa6ebb76863bdb1d11380bf032a6a1fc1b919194f041a5133852891"
        },
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            "cell_metadata_filter": "-all",
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            "notebook_metadata_filter": "-all"
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        "kernelspec": {
            "display_name": "Python 3.7.9 ('venv': venv)",
            "language": "python",
            "name": "python3"
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        "lang": "pl",
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            "codemirror_mode": {
                "name": "ipython",
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            "nbconvert_exporter": "python",
            "pygments_lexer": "ipython3",
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        },
        "subtitle": "9.Zarządzanie dialogiem z wykorzystaniem reguł[laboratoria]",
        "title": "Systemy Dialogowe",
        "year": "2021"
    },
    "nbformat": 4,
    "nbformat_minor": 4
}