{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4af8e091",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "class Rules_DST(): \n",
    "\n",
    "    def __init__(self):\n",
    "        self.state = json.load(open('data.json'))\n",
    "\n",
    "    def update_user(self, user_acts=None):\n",
    "        for intent, domain, slot, value in user_acts:\n",
    "            domain = domain.lower()\n",
    "            intent = intent.lower()\n",
    "            slot = slot.lower()\n",
    "            if intent == 'start_conversation':\n",
    "                continue\n",
    "\n",
    "            elif intent == 'end_conversation':\n",
    "                self.state = json.load(open('data.json'))\n",
    "            elif domain not in self.state['belief_state']:\n",
    "                continue\n",
    "                \n",
    "            \n",
    "            elif 'inform' in intent:\n",
    "                if (slot == 'inform'):\n",
    "                    continue\n",
    "                \n",
    "                if(domain in slot):\n",
    "                    slot.replace(domain + \"/\", '')\n",
    "\n",
    "                domain_dic = self.state['belief_state'][domain]\n",
    "                if slot in domain_dic:\n",
    "                    self.state['belief_state'][domain][slot] = value\n",
    "  \n",
    "                    \n",
    "            elif intent == 'request':\n",
    "                if domain not in self.state['request_state']:\n",
    "                    self.state['request_state'][domain] = {}\n",
    "                if slot not in self.state['request_state'][domain]:\n",
    "                    self.state['request_state'][domain][slot] = 0\n",
    "                else:\n",
    "                    self.state['request_state'][domain][slot] = value\n",
    "                    \n",
    "            elif intent == 'start_conversation':\n",
    "                self.state[\"user_action\"].append([intent, domain, slot, value])\n",
    "                continue\n",
    "\n",
    "            elif intent == 'end_conversation':\n",
    "                self.state = json.load(open('data.json'))\n",
    "                \n",
    "            self.state[\"user_action\"].append([intent, domain, slot, value])\n",
    "        return self.state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "09903205",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'user_action': [],\n",
       " 'system_action': [],\n",
       " 'belief_state': {'food': {'name': '',\n",
       "   'type': '',\n",
       "   'price range': '',\n",
       "   'size': '',\n",
       "   'ingredients': ''},\n",
       "  'drink': {'name': '', 'price range': '', 'size': ''},\n",
       "  'sauce': {'name': '', 'price range': '', 'size': ''},\n",
       "  'order': {'type': '',\n",
       "   'price range': '',\n",
       "   'restaurant_name': '',\n",
       "   'area': '',\n",
       "   'book time': '',\n",
       "   'book day': ''},\n",
       "  'booking': {'restaurant_name': '',\n",
       "   'area': '',\n",
       "   'book time': '',\n",
       "   'book day': '',\n",
       "   'book people': ''},\n",
       "  'payment': {'type': '', 'amount': '', 'vat': ''}},\n",
       " 'request_state': {},\n",
       " 'terminated': False,\n",
       " 'history': []}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst = Rules_DST()\n",
    "dst.state"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ec2b40d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst.state['user_action']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ca5ec2f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': '', 'type': '', 'price range': '', 'size': '', 'ingredients': ''}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst.update_user([['star_conversation',\"\",\"\",\"\"], ['inform', 'drink', 'size', 'duża']])\n",
    "dst.state['belief_state']['food']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2a36fa8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[['inform', 'drink', 'size', 'duża']]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst.state['user_action']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "67fd77b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'drink': {'price range': 0}}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst.update_user([['request', 'drink', 'price range', '?']])\n",
    "dst.state['request_state']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "834ebb03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'name': '',\n",
       " 'type': 'pizza',\n",
       " 'price range': '',\n",
       " 'size': 'duża',\n",
       " 'ingredients': ''}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dst.update_user([['inform', 'food', 'type', 'pizza'], ['inform', 'food', 'size', 'duża']])\n",
    "dst.state['belief_state']['food']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4b61083c",
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import defaultdict\n",
    "import jmespath\n",
    "\n",
    "class DP():\n",
    "    def __init__(self):\n",
    "        with open('database.json', encoding='utf-8-sig') as json_file:\n",
    "            self.db =  json.load(json_file)\n",
    "    \n",
    "\n",
    "    def predict(self, state):\n",
    "        self.results = []\n",
    "        system_action = defaultdict(list)\n",
    "        user_action = defaultdict(list)\n",
    "        system_acts = []\n",
    "        for idx in range(len(state['user_action'])):\n",
    "            intent, domain, slot, value = state['user_action'][idx]\n",
    "            user_action[(domain, intent)].append((slot, value))\n",
    "\n",
    "        for user_act in user_action:\n",
    "            system_acts.append(self.update_system_action(user_act, user_action, state, system_action))\n",
    "        state['system_action'] = system_acts\n",
    "        return system_acts[-1]\n",
    "\n",
    "\n",
    "    def update_system_action(self, user_act, user_action, state, system_action):\n",
    "        \n",
    "        domain, intent = user_act    \n",
    "        \n",
    "        #Reguła 3\n",
    "        if intent == 'end_conversation':\n",
    "            return None\n",
    "        \n",
    "        constraints = [(slot, value) for slot, value in state['belief_state'][domain].items() if value != '']\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",
    "                    if slot[0] in self.results[0]:\n",
    "                        system_action[(domain, 'Inform')].append([slot[0], self.results[0].get(slot[0], 'unknown')])\n",
    "\n",
    "        # Reguła 2\n",
    "        elif intent == 'inform':\n",
    "            if len(constraints)>1:\n",
    "                arg=f\"{constraints[0]}\".replace(f\"\\'{constraints[0][0]}\\'\",f\"{constraints[0][0]}\")\n",
    "                arg = arg.replace(\"[\",\"\").replace(\"]\",\"\")\n",
    "                for cons in constraints[1:]:\n",
    "                    arg+=f\" && contains{cons}\".replace(f\"\\'{cons[0]}\\'\",f\"{cons[0]}\").replace(\"[\",\"\").replace(\"]\",\"\")\n",
    "            else:\n",
    "                arg=f\"{constraints}\".replace(f\"\\'{constraints[0]}\\'\",f\"{constraints[0]}\").replace(\"[\",\"\").replace(\"]\",\"\").replace(\"(\\'\",\"(\").replace(\"\\',\",\",\")  \n",
    "            self.results = jmespath.search(f\"database.{domain}[?contains{arg} == `true` ]\", self.db) \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 [\"food\", \"drink\", \"police\", \"sauce\", \"order\", \"booking\", \"payment\"]:\n",
    "                    system_action[(domain, 'Recommend')].append(['Name', choice['name']])\n",
    "        return system_action\n",
    "                    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e587661a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(list,\n",
       "            {('drink', 'Inform'): [['Choice', '1'],\n",
       "              ['price range', 'średnia']],\n",
       "             ('drink', 'Recommend'): [['Name', 'lemoniada']],\n",
       "             ('food', 'Inform'): [['Choice', '4']],\n",
       "             ('food', 'Recommend'): [['Name', 'pizza margherita']]})"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dp= DP()\n",
    "dp.predict(dst.state)"
   ]
  }
 ],
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