Agent.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "87a9a772",
   "metadata": {},
   "outputs": [],
   "source": [
    "import gurobipy as gp\n",
    "from gurobipy import GRB\n",
    "from eventlet.timeout import Timeout\n",
    "\n",
    "# import auxillary packages\n",
    "import requests  # for loading the example source code\n",
    "import openai\n",
    "import json\n",
    "\n",
    "# import flaml and autogen\n",
    "from flaml import autogen\n",
    "from flaml.autogen.agentchat import Agent, UserProxyAgent\n",
    "from EnergySaverLLM.Agent import ChargingAgent, reset_params_file\n",
    "from flaml.autogen.code_utils import extract_code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9adda55a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# global params_filepath\n",
    "params_filepath = \"EnergySaverLLM/Model/params/EVCharging.json\"\n",
    "params_filepath_backup = \"EnergySaverLLM/Model/params/EVCharging_original.json\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d3ce236c",
   "metadata": {},
   "outputs": [],
   "source": [
    "reset_params_file(params_filepath, params_filepath_backup)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1cb9a00f",
   "metadata": {},
   "outputs": [],
   "source": [
    "config_list = autogen.config_list_from_json(\n",
    "    env_or_file = \"OAI_CONFIG_LIST\",\n",
    "    filter_dict={\n",
    "        \"model\": [\"gpt-4\", \"gpt-3.5-turbo-16k\"],\n",
    "    },\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "be661b6d",
   "metadata": {},
   "outputs": [],
   "source": [
    "config_list_gpt3_5 = autogen.config_list_from_json(\n",
    "    env_or_file = \"OAI_CONFIG_LIST\",\n",
    "    filter_dict={\n",
    "        \"model\": [\"gpt-3.5-turbo-16k\"],\n",
    "    },\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ebbceda1",
   "metadata": {},
   "outputs": [],
   "source": [
    "autogen.oai.ChatCompletion.start_logging()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2e94b994",
   "metadata": {},
   "outputs": [],
   "source": [
    "code_path = \"EnergySaverLLM/Model/EVCharging.py\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "76c37670",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open(code_path) as f:\n",
    "    code = f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e9adce8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "example_qa = \"\"\"\n",
    "----------\n",
    "Instruction: Charge the car till 9 AM.\n",
    "Answer Code:\n",
    "```JSON\n",
    "\"end_charge_time\": 9\n",
    "```\n",
    "\n",
    "----------\n",
    "Question: Charge the car to full charge by 9 AM\n",
    "Answer Code:\n",
    "```JSON\n",
    "\"end_charge\": 1.00,\n",
    "\"end_charge_time\": 9\n",
    "```\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3b9b6c19",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'0': 0.3, '1': 0.3, '2': 0.3, '3': 0.3, '4': 0.3, '5': 0.3, '6': 0.3, '7': 0.35, '8': 0.35, '9': 0.35, '10': 0.35, '11': 0.3, '12': 0.3, '13': 0.3, '14': 0.3, '15': 0.3, '16': 0.3, '17': 0.3, '18': 0.3, '19': 0.35, '20': 0.35, '21': 0.35, '22': 0.3, '23': 0.3}\n",
      "Restricted license - for non-production use only - expires 2024-10-28\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x7c396a84\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 4e+01]\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.06 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 1: 327.6 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.276000000000e+02, best bound 3.276000000000e+02, gap 0.0000%\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x7c396a84\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 4e+01]\n",
      "\n",
      "\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.02 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 1: 327.6 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.276000000000e+02, best bound 3.276000000000e+02, gap 0.0000%\n",
      "Optimal Charging Schedule:\n",
      "Scheduled consumption at Hour 22 : 11 KWH\n",
      "Scheduled consumption at Hour 24 : 9 KWH\n",
      "Scheduled consumption at Hour 25 : 11 KWH\n",
      "Scheduled consumption at Hour 26 : 11 KWH\n"
     ]
    }
   ],
   "source": [
    "agent = ChargingAgent(\n",
    "    name=\"Tesla Charging Example\",\n",
    "    source_code=code,\n",
    "    example_qa=example_qa,\n",
    "    json_filepath=params_filepath,\n",
    "    llm_config={\n",
    "        \"request_timeout\": 600,\n",
    "        \"seed\": 42,\n",
    "        \"config_list\": config_list,\n",
    "    }\n",
    ")\n",
    "\n",
    "user = UserProxyAgent(\n",
    "    \"user\", max_consecutive_auto_reply=0,\n",
    "    human_input_mode=\"NEVER\", code_execution_config=False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "80866c79",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33muser\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Increase Electricity cost by 30%\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "\n",
      "Answer JSON:\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "```JSON\n",
      "{\n",
      "    \"elec_cost\": {\n",
      "        \"0\": 0.39,\n",
      "        \"1\": 0.39,\n",
      "        \"2\": 0.39,\n",
      "        \"3\": 0.39,\n",
      "        \"4\": 0.39,\n",
      "        \"5\": 0.39,\n",
      "        \"6\": 0.39,\n",
      "        \"7\": 0.455,\n",
      "        \"8\": 0.455,\n",
      "        \"9\": 0.455,\n",
      "        \"10\": 0.455,\n",
      "        \"11\": 0.39,\n",
      "        \"12\": 0.39,\n",
      "        \"13\": 0.39,\n",
      "        \"14\": 0.39,\n",
      "        \"15\": 0.39,\n",
      "        \"16\": 0.39,\n",
      "        \"17\": 0.39,\n",
      "        \"18\": 0.39,\n",
      "        \"19\": 0.45,\n",
      "        \"20\": 0.45,\n",
      "        \"21\": 0.45,\n",
      "        \"22\": 0.39,\n",
      "        \"23\": 0.39\n",
      "    }\n",
      "}\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "{'0': 0.39, '1': 0.39, '2': 0.39, '3': 0.39, '4': 0.39, '5': 0.39, '6': 0.39, '7': 0.455, '8': 0.455, '9': 0.455, '10': 0.455, '11': 0.39, '12': 0.39, '13': 0.39, '14': 0.39, '15': 0.39, '16': 0.39, '17': 0.39, '18': 0.39, '19': 0.45, '20': 0.45, '21': 0.45, '22': 0.39, '23': 0.39}\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x8868b277\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [4e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 4e+01]\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.00 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 1: 331.38 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.313800000000e+02, best bound 3.313800000000e+02, gap 0.0000%\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x8868b277\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [4e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 4e+01]\n",
      "\n",
      "\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 1: 331.38 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.313800000000e+02, best bound 3.313800000000e+02, gap 0.0000%\n",
      "Optimal Charging Schedule:\n",
      "Scheduled consumption at Hour 22 : 11 KWH\n",
      "Scheduled consumption at Hour 24 : 9 KWH\n",
      "Scheduled consumption at Hour 25 : 11 KWH\n",
      "Scheduled consumption at Hour 26 : 11 KWH\n",
      "\u001b[33mOptimization problem solved. The objective value is: 331.38\u001b[0m\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to interpreter):\n",
      "\n",
      "Here are the execution results: Optimization problem solved. The objective value is: 331.38\n",
      "\n",
      "Can you organize these information to a human readable answer?\n",
      "Remember to compare the new results to the original results you obtained in the\n",
      "beginning. A lower objective value is better here.\n",
      "\n",
      "--- HUMAN READABLE ANSWER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33minterpreter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Sure, after increasing the electricity cost by 30%, the optimization problem was successfully solved again. The new objective value is 331.38. When we compare this new value to the original value of 327.6, we can see that it has increased. This means the overall cost has increased after the change, which is consistent with the fact that a higher electricity cost would generally lead to a higher total cost. Please note that a lower objective value is preferable in this context, so the increase indicates a less favorable outcome.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to user):\n",
      "\n",
      "Sure, after increasing the electricity cost by 30%, the optimization problem was successfully solved again. The new objective value is 331.38. When we compare this new value to the original value of 327.6, we can see that it has increased. This means the overall cost has increased after the change, which is consistent with the fact that a higher electricity cost would generally lead to a higher total cost. Please note that a lower objective value is preferable in this context, so the increase indicates a less favorable outcome.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "user.initiate_chat(agent, message=\"Increase Electricity cost by 30%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9fc8be8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33muser\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Complete charging battery to 100% and reduce carbon cost by 10%\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "\n",
      "Answer JSON:\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "```JSON\n",
      "\"end_charge\": 1.0,\n",
      "\"carbon_cost\": {\n",
      "    \"0\": 22.5,\n",
      "    \"1\": 22.5,\n",
      "    \"2\": 22.5,\n",
      "    \"3\": 22.5,\n",
      "    \"4\": 22.5,\n",
      "    \"5\": 22.5,\n",
      "    \"6\": 22.5,\n",
      "    \"7\": 22.5,\n",
      "    \"8\": 22.5,\n",
      "    \"9\": 22.5,\n",
      "    \"10\": 22.5,\n",
      "    \"11\": 22.5,\n",
      "    \"12\": 22.5,\n",
      "    \"13\": 22.5,\n",
      "    \"14\": 22.5,\n",
      "    \"15\": 22.5,\n",
      "    \"16\": 22.5,\n",
      "    \"17\": 22.5,\n",
      "    \"18\": 22.5,\n",
      "    \"19\": 22.5,\n",
      "    \"20\": 22.5,\n",
      "    \"21\": 22.5,\n",
      "    \"22\": 22.5,\n",
      "    \"23\": 22.5\n",
      "}\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "{'0': 0.39, '1': 0.39, '2': 0.39, '3': 0.39, '4': 0.39, '5': 0.39, '6': 0.39, '7': 0.455, '8': 0.455, '9': 0.455, '10': 0.455, '11': 0.39, '12': 0.39, '13': 0.39, '14': 0.39, '15': 0.39, '16': 0.39, '17': 0.39, '18': 0.39, '19': 0.45, '20': 0.45, '21': 0.45, '22': 0.39, '23': 0.39}\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x6935dce7\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [4e-01, 1e+00]\n",
      "  Objective range  [7e+00, 7e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 6e+01]\n",
      "Presolve removed 0 rows and 47 columns\n",
      "Presolve time: 0.00s\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 0\n",
      "\n",
      "Model is infeasible\n",
      "Best objective -, best bound -, gap -\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x6935dce7\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [4e-01, 1e+00]\n",
      "  Objective range  [7e+00, 7e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 6e+01]\n",
      "Presolve removed 0 rows and 47 columns\n",
      "Presolve time: 0.00s\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.02 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 0\n",
      "\n",
      "Model is infeasible\n",
      "Best objective -, best bound -, gap -\n",
      "Not solved to optimality. Optimization status: 3\n",
      "\n",
      "Computing Irreducible Inconsistent Subsystem (IIS)...\n",
      "\n",
      "           Constraints          |            Bounds           |  Runtime\n",
      "      Min       Max     Guess   |   Min       Max     Guess   |\n",
      "--------------------------------------------------------------------------\n",
      "        0         2         -         0        96         -           0s\n",
      "        2         2         2        14        14        14           0s\n",
      "\n",
      "IIS computed: 2 constraints, 14 bounds\n",
      "IIS runtime: 0.02 seconds (0.00 work units)\n",
      "\u001b[33minfeasible\n",
      "Conflicting Constraints:\n",
      "['R0', 'R1']\u001b[0m\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to interpreter):\n",
      "\n",
      "Here are the execution results: infeasible\n",
      "Conflicting Constraints:\n",
      "['R0', 'R1']\n",
      "\n",
      "Can you organize these information to a human readable answer?\n",
      "Remember to compare the new results to the original results you obtained in the\n",
      "beginning. A lower objective value is better here.\n",
      "\n",
      "--- HUMAN READABLE ANSWER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33minterpreter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "The latest execution result shows that the optimization problem could not be solved due to infeasible constraints. It seems there are conflicts between some constraints, specifically 'R0' and 'R1'.\n",
      "\n",
      "To compare with the original results, initially the problem was solved successfully with an objective value of 327.6, indicating a better solution. This objective value represents the cost associated with the optimization problem. Lower objective values are better because they signify lower costs.\n",
      "\n",
      "However, after attempting to adjust the model to complete charging the battery to 100% and reduce carbon cost by 10%, as per your request, the model turned infeasible, meaning that there's no possible solution under the newly set constraints. \n",
      "\n",
      "To address this issue, you might need to loosen the conflicting constraints, or adjust the goal to be more feasible within the defined constraints.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to user):\n",
      "\n",
      "The latest execution result shows that the optimization problem could not be solved due to infeasible constraints. It seems there are conflicts between some constraints, specifically 'R0' and 'R1'.\n",
      "\n",
      "To compare with the original results, initially the problem was solved successfully with an objective value of 327.6, indicating a better solution. This objective value represents the cost associated with the optimization problem. Lower objective values are better because they signify lower costs.\n",
      "\n",
      "However, after attempting to adjust the model to complete charging the battery to 100% and reduce carbon cost by 10%, as per your request, the model turned infeasible, meaning that there's no possible solution under the newly set constraints. \n",
      "\n",
      "To address this issue, you might need to loosen the conflicting constraints, or adjust the goal to be more feasible within the defined constraints.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "user.initiate_chat(agent, message=\"Complete charging battery to 100% and reduce carbon cost by 10%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e162e7df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33muser\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Complete charging battery to 100% by 9 AM tomorrow\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "\n",
      "Answer JSON:\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "\"end_charge\": 1.0,\n",
      "\"end_charge_time\": 9\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "{'0': 0.3, '1': 0.3, '2': 0.3, '3': 0.3, '4': 0.3, '5': 0.3, '6': 0.3, '7': 0.35, '8': 0.35, '9': 0.35, '10': 0.35, '11': 0.3, '12': 0.3, '13': 0.3, '14': 0.3, '15': 0.3, '16': 0.3, '17': 0.3, '18': 0.3, '19': 0.35, '20': 0.35, '21': 0.35, '22': 0.3, '23': 0.3}\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x7b4bbd5a\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 6e+01]\n",
      "Found heuristic solution: objective 436.8000000\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 1: 436.8 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 4.368000000000e+02, best bound 4.368000000000e+02, gap 0.0000%\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x7b4bbd5a\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 6e+01]\n",
      "\n",
      "Loaded MIP start from previous solve with objective 436.8\n",
      "\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 2: 436.8 436.8 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 4.368000000000e+02, best bound 4.368000000000e+02, gap 0.0000%\n",
      "Optimal Charging Schedule:\n",
      "Scheduled consumption at Hour 15 : 1 KWH\n",
      "Scheduled consumption at Hour 16 : 11 KWH\n",
      "Scheduled consumption at Hour 17 : 11 KWH\n",
      "Scheduled consumption at Hour 18 : 11 KWH\n",
      "Scheduled consumption at Hour 28 : 11 KWH\n",
      "Scheduled consumption at Hour 29 : 11 KWH\n",
      "\u001b[33mOptimization problem solved. The objective value is: 436.8\u001b[0m\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to interpreter):\n",
      "\n",
      "Here are the execution results: Optimization problem solved. The objective value is: 436.8\n",
      "\n",
      "Can you organize these information to a human readable answer?\n",
      "Remember to compare the new results to the original results you obtained in the\n",
      "beginning. A lower objective value is better here.\n",
      "\n",
      "--- HUMAN READABLE ANSWER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33minterpreter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "The original objective value was 327.6 and the new objective value is 436.8. This means that the new solution is worse than the original solution.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to user):\n",
      "\n",
      "The original objective value was 327.6 and the new objective value is 436.8. This means that the new solution is worse than the original solution.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "user.initiate_chat(agent, message=\"Complete charging battery to 100% by 9 AM tomorrow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d9c981af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33muser\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Complete charging battery to 100% by 9 AM tomorrow\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "\n",
      "Answer Code:\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "```python\n",
      "end_charge_level = 1\n",
      "end_time_H = 9\n",
      "this_charge_KWH = (end_charge_level - start_charge_level) * total_battery_capacity\n",
      "upper_bounds[curr_time_H:end_time_H] = [max_power_KW] * (end_time_H - curr_time_H)\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to safeguard):\n",
      "\n",
      "\n",
      "--- Code ---\n",
      "end_charge_level = 1\n",
      "end_time_H = 9\n",
      "this_charge_KWH = (end_charge_level - start_charge_level) * total_battery_capacity\n",
      "upper_bounds[curr_time_H:end_time_H] = [max_power_KW] * (end_time_H - curr_time_H)\n",
      "\n",
      "--- One-Word Answer: SAFE or DANGER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33msafeguard\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "SAFE\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "{'0': 0.3, '1': 0.3, '2': 0.3, '3': 0.3, '4': 0.3, '5': 0.3, '6': 0.3, '7': 0.35, '8': 0.35, '9': 0.35, '10': 0.35, '11': 0.3, '12': 0.3, '13': 0.3, '14': 0.3, '15': 0.3, '16': 0.3, '17': 0.3, '18': 0.3, '19': 0.35, '20': 0.35, '21': 0.35, '22': 0.3, '23': 0.3}\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x85a39ae4\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 6e+01]\n",
      "Found heuristic solution: objective 437.9000000\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 2: 436.8 437.9 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 4.368000000000e+02, best bound 4.368000000000e+02, gap 0.0000%\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x85a39ae4\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 6e+01]\n",
      "\n",
      "\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 2: 436.8 437.9 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 4.368000000000e+02, best bound 4.368000000000e+02, gap 0.0000%\n",
      "Optimal Charging Schedule:\n",
      "Scheduled consumption at Hour 16 : 1 KWH\n",
      "Scheduled consumption at Hour 17 : 11 KWH\n",
      "Scheduled consumption at Hour 18 : 11 KWH\n",
      "Scheduled consumption at Hour 24 : 11 KWH\n",
      "Scheduled consumption at Hour 25 : 11 KWH\n",
      "Scheduled consumption at Hour 28 : 11 KWH\n",
      "\u001b[33mOptimization problem solved. The objective value is: 436.8\u001b[0m\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "Here are the execution results: Optimization problem solved. The objective value is: 436.8\n",
      "\n",
      "Can you organize these information to a human readable answer?\n",
      "Remember to compare the new results to the original results you obtained in the\n",
      "beginning.\n",
      "\n",
      "--- HUMAN READABLE ANSWER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "The optimization problem has been solved again with the new charging schedule. The objective value obtained is 436.8, which is higher than the original objective value of 382.2. This means that the new charging schedule incurs a higher cost. \n",
      "\n",
      "Please note that the answer code provided above only adjusts the charging schedule based on the user's request to charge the battery to 100% by 9:00 AM tomorrow. The objective value and the final charging schedule might be different depending on other constraints and the specific values of the parameters.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to user):\n",
      "\n",
      "The optimization problem has been solved again with the new charging schedule. The objective value obtained is 436.8, which is higher than the original objective value of 382.2. This means that the new charging schedule incurs a higher cost. \n",
      "\n",
      "Please note that the answer code provided above only adjusts the charging schedule based on the user's request to charge the battery to 100% by 9:00 AM tomorrow. The objective value and the final charging schedule might be different depending on other constraints and the specific values of the parameters.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "user.initiate_chat(agent, message=\"Complete charging battery by 9 PM\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8784224d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33muser\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Reduce max allowed electricity cost to 15 dollars\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "\n",
      "Answer JSON:\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "```JSON\n",
      "\"max_energy_cost\": 15\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "{'0': 0.3, '1': 0.3, '2': 0.3, '3': 0.3, '4': 0.3, '5': 0.3, '6': 0.3, '7': 0.35, '8': 0.35, '9': 0.35, '10': 0.35, '11': 0.3, '12': 0.3, '13': 0.3, '14': 0.3, '15': 0.3, '16': 0.3, '17': 0.3, '18': 0.3, '19': 0.35, '20': 0.35, '21': 0.35, '22': 0.3, '23': 0.3}\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0xa2a065f5\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 4e+01]\n",
      "Found heuristic solution: objective 327.6000000\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.00 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 1: 327.6 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.276000000000e+02, best bound 3.276000000000e+02, gap 0.0000%\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0xa2a065f5\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 4e+01]\n",
      "\n",
      "Loaded MIP start from previous solve with objective 327.6\n",
      "\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.03 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 2: 327.6 327.6 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.276000000000e+02, best bound 3.276000000000e+02, gap 0.0000%\n",
      "Optimal Charging Schedule:\n",
      "Scheduled consumption at Hour 14 : 9 KWH\n",
      "Scheduled consumption at Hour 15 : 11 KWH\n",
      "Scheduled consumption at Hour 16 : 11 KWH\n",
      "Scheduled consumption at Hour 17 : 11 KWH\n",
      "\u001b[33mOptimization problem solved. The objective value is: 327.6\u001b[0m\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to interpreter):\n",
      "\n",
      "Here are the execution results: Optimization problem solved. The objective value is: 327.6\n",
      "\n",
      "Can you organize these information to a human readable answer?\n",
      "Remember to compare the new results to the original results you obtained in the\n",
      "beginning. A lower objective value is better here.\n",
      "\n",
      "--- HUMAN READABLE ANSWER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33minterpreter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "After reducing the maximum allowed electricity cost to 15 dollars as you requested, the optimization problem was solved again. However, the objective value remained at 327.6. This suggests that the additional restriction you imposed did not lead to a lower overall cost of electricity in the optimization model. Thus, it appears that the original configuration was already well optimized given your cost constraint.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to user):\n",
      "\n",
      "After reducing the maximum allowed electricity cost to 15 dollars as you requested, the optimization problem was solved again. However, the objective value remained at 327.6. This suggests that the additional restriction you imposed did not lead to a lower overall cost of electricity in the optimization model. Thus, it appears that the original configuration was already well optimized given your cost constraint.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "user.initiate_chat(agent, message=\"Reduce max allowed electricity cost to 15 dollars\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "88d8db60",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33muser\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Charge the car to full charge by 6 AM tomorrow\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "\n",
      "Answer Code:\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "```python\n",
      "end_charge_level = 1\n",
      "this_charge_KWH = (end_charge_level-start_charge_level)*total_battery_capacity\n",
      "model.addConstr(sum(x[i] for i in keys) == this_charge_KWH)\n",
      "end_time_H = 30\n",
      "upper_bounds[curr_time_H:end_time_H] = [max_power_KW] * (end_time_H - curr_time_H)\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to safeguard):\n",
      "\n",
      "\n",
      "--- Code ---\n",
      "end_charge_level = 1\n",
      "this_charge_KWH = (end_charge_level-start_charge_level)*total_battery_capacity\n",
      "model.addConstr(sum(x[i] for i in keys) == this_charge_KWH)\n",
      "end_time_H = 30\n",
      "upper_bounds[curr_time_H:end_time_H] = [max_power_KW] * (end_time_H - curr_time_H)\n",
      "\n",
      "--- One-Word Answer: SAFE or DANGER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33msafeguard\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "SAFE\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "{'0': 0.3, '1': 0.3, '2': 0.3, '3': 0.3, '4': 0.3, '5': 0.3, '6': 0.3, '7': 0.35, '8': 0.35, '9': 0.35, '10': 0.35, '11': 0.3, '12': 0.3, '13': 0.3, '14': 0.3, '15': 0.3, '16': 0.3, '17': 0.3, '18': 0.3, '19': 0.35, '20': 0.35, '21': 0.35, '22': 0.3, '23': 0.3}\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0x959f99f2\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 5e+01]\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 1: 382.2 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.822000000000e+02, best bound 3.822000000000e+02, gap 0.0000%\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 3 rows, 48 columns and 144 nonzeros\n",
      "Model fingerprint: 0x5b537287\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 6e+01]\n",
      "\n",
      "MIP start from previous solve did not produce a new incumbent solution\n",
      "MIP start from previous solve violates constraint R2 by 7.000000000\n",
      "\n",
      "Presolve removed 0 rows and 46 columns\n",
      "Presolve time: 0.00s\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 0\n",
      "\n",
      "Model is infeasible\n",
      "Best objective -, best bound -, gap -\n",
      "Not solved to optimality. Optimization status: 3\n",
      "\n",
      "Computing Irreducible Inconsistent Subsystem (IIS)...\n",
      "\n",
      "           Constraints          |            Bounds           |  Runtime\n",
      "      Min       Max     Guess   |   Min       Max     Guess   |\n",
      "--------------------------------------------------------------------------\n",
      "        0         3         -         0        96         -           0s\n",
      "        2         2         2         0         0         0           0s\n",
      "\n",
      "IIS computed: 2 constraints, 0 bounds\n",
      "IIS runtime: 0.04 seconds (0.00 work units)\n",
      "\u001b[33minfeasible\n",
      "Conflicting Constraints:\n",
      "['R1', 'R2']\u001b[0m\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "Here are the execution results: infeasible\n",
      "Conflicting Constraints:\n",
      "['R1', 'R2']\n",
      "\n",
      "Can you organize these information to a human readable answer?\n",
      "Remember to compare the new results to the original results you obtained in the\n",
      "beginning.\n",
      "\n",
      "--- HUMAN READABLE ANSWER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "It appears that the changes requested have resulted in a situation where the constraints of the problem are conflicting, rendering the problem infeasible. \n",
      "\n",
      "The conflict is between constraints 'R1' and 'R2'. These were most likely constraints set in the model that can't all be satisfied simultaneously given the new requirement of charging the car to a full charge by 6 AM tomorrow.\n",
      "\n",
      "In the original model, we were minimizing the cost and we got an optimal charging schedule based on this objective. However, after the changes, the model is not achievable as it exceeds the capacity or time constraints. Therefore, it is not feasible to change the charging to be full by 6 AM tomorrow given the current constraints and parameters.\n",
      "\n",
      "Making these adjustments would require increasing the available charging time, increasing the vehicle's charging power, or decreasing the desired charge level. \n",
      "\n",
      "Suggestions for change could include charging at a larger power level, extending the charging duration, or reducing the charging level.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to user):\n",
      "\n",
      "It appears that the changes requested have resulted in a situation where the constraints of the problem are conflicting, rendering the problem infeasible. \n",
      "\n",
      "The conflict is between constraints 'R1' and 'R2'. These were most likely constraints set in the model that can't all be satisfied simultaneously given the new requirement of charging the car to a full charge by 6 AM tomorrow.\n",
      "\n",
      "In the original model, we were minimizing the cost and we got an optimal charging schedule based on this objective. However, after the changes, the model is not achievable as it exceeds the capacity or time constraints. Therefore, it is not feasible to change the charging to be full by 6 AM tomorrow given the current constraints and parameters.\n",
      "\n",
      "Making these adjustments would require increasing the available charging time, increasing the vehicle's charging power, or decreasing the desired charge level. \n",
      "\n",
      "Suggestions for change could include charging at a larger power level, extending the charging duration, or reducing the charging level.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "user.initiate_chat(agent, message=\"Charge the car to full charge by 6 AM tomorrow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "922fb36e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[33muser\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Charge the car by 9 AM tomorrow\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "\n",
      "Answer Code:\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "```python\n",
      "end_time_H = 33\n",
      "upper_bounds = [0]*len(elec_costs)\n",
      "upper_bounds[curr_time_H:end_time_H] = [max_power_KW] * (end_time_H - curr_time_H)\n",
      "```\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to safeguard):\n",
      "\n",
      "\n",
      "--- Code ---\n",
      "end_time_H = 33\n",
      "upper_bounds = [0]*len(elec_costs)\n",
      "upper_bounds[curr_time_H:end_time_H] = [max_power_KW] * (end_time_H - curr_time_H)\n",
      "\n",
      "--- One-Word Answer: SAFE or DANGER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33msafeguard\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "SAFE\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "{'0': 0.3, '1': 0.3, '2': 0.3, '3': 0.3, '4': 0.3, '5': 0.3, '6': 0.3, '7': 0.35, '8': 0.35, '9': 0.35, '10': 0.35, '11': 0.3, '12': 0.3, '13': 0.3, '14': 0.3, '15': 0.3, '16': 0.3, '17': 0.3, '18': 0.3, '19': 0.35, '20': 0.35, '21': 0.35, '22': 0.3, '23': 0.3}\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0xab6986cb\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 5e+01]\n",
      "Found heuristic solution: objective 382.4500000\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.02 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 2: 382.2 382.45 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.822000000000e+02, best bound 3.822000000000e+02, gap 0.0000%\n",
      "Gurobi Optimizer version 10.0.3 build v10.0.3rc0 (mac64[arm])\n",
      "\n",
      "CPU model: Apple M1\n",
      "Thread count: 8 physical cores, 8 logical processors, using up to 8 threads\n",
      "\n",
      "Optimize a model with 2 rows, 48 columns and 96 nonzeros\n",
      "Model fingerprint: 0xab6986cb\n",
      "Variable types: 0 continuous, 48 integer (0 binary)\n",
      "Coefficient statistics:\n",
      "  Matrix range     [3e-01, 1e+00]\n",
      "  Objective range  [8e+00, 8e+00]\n",
      "  Bounds range     [1e+01, 1e+01]\n",
      "  RHS range        [2e+01, 5e+01]\n",
      "\n",
      "\n",
      "Presolve removed 2 rows and 48 columns\n",
      "Presolve time: 0.00s\n",
      "Presolve: All rows and columns removed\n",
      "\n",
      "Explored 0 nodes (0 simplex iterations) in 0.01 seconds (0.00 work units)\n",
      "Thread count was 1 (of 8 available processors)\n",
      "\n",
      "Solution count 2: 382.2 382.45 \n",
      "\n",
      "Optimal solution found (tolerance 1.00e-04)\n",
      "Best objective 3.822000000000e+02, best bound 3.822000000000e+02, gap 0.0000%\n",
      "Optimal Charging Schedule:\n",
      "Scheduled consumption at Hour 22 : 11 KWH\n",
      "Scheduled consumption at Hour 23 : 11 KWH\n",
      "Scheduled consumption at Hour 24 : 11 KWH\n",
      "Scheduled consumption at Hour 26 : 5 KWH\n",
      "Scheduled consumption at Hour 27 : 11 KWH\n",
      "\u001b[33mOptimization problem solved. The objective value is: 382.2\u001b[0m\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to writer):\n",
      "\n",
      "Here are the execution results: Optimization problem solved. The objective value is: 382.2\n",
      "\n",
      "Can you organize these information to a human readable answer?\n",
      "Remember to compare the new results to the original results you obtained in the\n",
      "beginning.\n",
      "\n",
      "--- HUMAN READABLE ANSWER ---\n",
      "\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mwriter\u001b[0m (to Tesla Charging Example):\n",
      "\n",
      "Yes, based on the new scheduled end charging time which is 9 AM tomorrow, the optimization model has rescheduled the charging times within the permissible limit. However, there's no change in the objective value which is still 382.2. This implies that even though the charging period has been prolonged, the model is able to meet the target charge by choosing the least costly hours, hence the total cost didn't change. This is because the model is capable of selecting the optimal hours with the minimum cost within the allowed charging period.\n",
      "\n",
      "--------------------------------------------------------------------------------\n",
      "\u001b[33mTesla Charging Example\u001b[0m (to user):\n",
      "\n",
      "Yes, based on the new scheduled end charging time which is 9 AM tomorrow, the optimization model has rescheduled the charging times within the permissible limit. However, there's no change in the objective value which is still 382.2. This implies that even though the charging period has been prolonged, the model is able to meet the target charge by choosing the least costly hours, hence the total cost didn't change. This is because the model is capable of selecting the optimal hours with the minimum cost within the allowed charging period.\n",
      "\n",
      "--------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "user.initiate_chat(agent, message=\"Charge the car by 9 AM tomorrow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "52f519f7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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