3.8 Chatbot.ipynb

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   "source": [
    "# ChatBot\n",
    "We can use LLMs to build our own custom chatbot, we can use this in our applications like AI order taker at restaurants or service agent etc."
   ]
  },
  {
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   "source": [
    "import os\n",
    "import openai\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "_ = load_dotenv(find_dotenv()) # read local .env file\n",
    "\n",
    "openai.api_key  = os.getenv('OPENAI_API_KEY')"
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   "source": [
    "def get_completion(prompt, model=\"gpt-3.5-turbo\"):\n",
    "    messages = [{\"role\": \"user\", \"content\": prompt}]\n",
    "    response = openai.ChatCompletion.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "        temperature=0, # this is the degree of randomness of the model's output\n",
    "    )\n",
    "    return response.choices[0].message[\"content\"]\n",
    "\n",
    "def get_completion_from_messages(messages, model=\"gpt-3.5-turbo\", temperature=0):\n",
    "    response = openai.ChatCompletion.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "        temperature=temperature, # this is the degree of randomness of the model's output\n",
    "    )\n",
    "#     print(str(response.choices[0].message))\n",
    "    return response.choices[0].message[\"content\"]"
   ]
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  {
   "cell_type": "markdown",
   "id": "935d654f-210b-485e-b3ae-90784d7a34d0",
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   "source": [
    "Here instead of passing a single prompt or text an an input and getting a single completion, we are going to pass in a list of messages and these messages can be variety of different roles."
   ]
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   "id": "cee681b7",
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   "source": [
    "messages =  [  \n",
    "{'role':'system', 'content':'You are an assistant that speaks like Shakespeare.'},    \n",
    "{'role':'user', 'content':'tell me a joke'},   \n",
    "{'role':'assistant', 'content':'Why did the chicken cross the road'},   \n",
    "{'role':'user', 'content':'I don\\'t know'}  ]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c82da79-7d07-4757-ac94-d56efb6eeaf2",
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   "source": [
    "This first message is the system message which gives an overall instruction, this helps in setting the behaviour and it is a high-level instruction for the conversation. After this we have turns between user and the assistant and this will continue to go on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "da45ea0f",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "To get to the other side! 'Tis a classic jest as old as time itself.\n"
     ]
    }
   ],
   "source": [
    "response = get_completion_from_messages(messages, temperature=1)\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ca733f8f",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hi Isa! It's nice to meet you. What's on your mind today?\n"
     ]
    }
   ],
   "source": [
    "messages =  [  \n",
    "{'role':'system', 'content':'You are friendly chatbot.'},    \n",
    "{'role':'user', 'content':'Hi, my name is Isa'}  ]\n",
    "response = get_completion_from_messages(messages, temperature=1)\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0ae595bc",
   "metadata": {
    "height": 98,
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I'm sorry, but I can't remember personal information like your name. However, I'm here to help you with any other questions or information you need!\n"
     ]
    }
   ],
   "source": [
    "messages =  [  \n",
    "{'role':'system', 'content':'You are friendly chatbot.'},    \n",
    "{'role':'user', 'content':'Yes,  can you remind me, What is my name?'}  ]\n",
    "response = get_completion_from_messages(messages, temperature=1)\n",
    "print(response)"
   ]
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   "cell_type": "code",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Your name is Isa! How can I assist you today, Isa?\n"
     ]
    }
   ],
   "source": [
    "messages =  [  \n",
    "{'role':'system', 'content':'You are friendly chatbot.'},\n",
    "{'role':'user', 'content':'Hi, my name is Isa'},\n",
    "{'role':'assistant', 'content': \"Hi Isa! It's nice to meet you. \\\n",
    "Is there anything I can help you with today?\"},\n",
    "{'role':'user', 'content':'Yes, you can remind me, What is my name?'}  ]\n",
    "response = get_completion_from_messages(messages, temperature=1)\n",
    "print(response)"
   ]
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   "cell_type": "markdown",
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   "source": [
    "# OrderBot\n",
    "We can automate the collection of user prompts and assistant responses to build a  OrderBot. The OrderBot will take orders at a pizza restaurant. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e76749ac",
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   "source": [
    "def collect_messages(_):\n",
    "    prompt = inp.value_input\n",
    "    inp.value = ''\n",
    "    context.append({'role':'user', 'content':f\"{prompt}\"})\n",
    "    response = get_completion_from_messages(context) \n",
    "    context.append({'role':'assistant', 'content':f\"{response}\"})\n",
    "    panels.append(\n",
    "        pn.Row('User:', pn.pane.Markdown(prompt, width=600)))\n",
    "    panels.append(\n",
    "        pn.Row('Assistant:', pn.pane.Markdown(response, width=600, style={'background-color': '#F6F6F6'})))\n",
    " \n",
    "    return pn.Column(*panels)\n"
   ]
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   "source": [
    "The above function will collects the user messages and collect the prompts and append it in a list called \"context\", then it will call the model with that conetxt everytime. The model responses is also added to the context. In this way the model will gain information to determine what to do next."
   ]
  },
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   "execution_count": 9,
   "id": "474b557c",
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i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/0.14.4/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) >= 0) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.3.min.js\", \"https://unpkg.com/@holoviz/panel@0.14.4/dist/panel.min.js\"];\n  var js_modules = [];\n  var css_urls = [\"https://cdn.holoviz.org/panel/0.14.4/dist/css/alerts.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/card.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/dataframe.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/debugger.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/json.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/loading.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/markdown.css\", \"https://cdn.holoviz.org/panel/0.14.4/dist/css/widgets.css\"];\n  var inline_js = [    function(Bokeh) {\n      inject_raw_css(\"\\n    .bk.pn-loading.arc:before {\\n      background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n      background-size: auto calc(min(50%, 400px));\\n    }\\n    \");\n    },    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, js_modules, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
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else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  function embed_document(root) {\n",
       "    var docs_json = 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   if ('event:button_click'.startsWith('event:')) {\\n      var value = true\\n    } else {\\n      var value = source['event:button_click'];\\n      value = value;\\n    }\\n    if (typeof value !== 'boolean' || source.labels !== ['Loading']) {\\n      value = true\\n    }\\n    var css_classes = target.css_classes.slice()\\n    var loading_css = ['pn-loading', 'arc']\\n    if (value) {\\n      for (var css of loading_css) {\\n        if (!(css in css_classes)) {\\n          css_classes.push(css)\\n        }\\n      }\\n    } else {\\n     for (var css of loading_css) {\\n        var index = css_classes.indexOf(css)\\n        if (index > -1) {\\n          css_classes.splice(index, 1)\\n        }\\n      }\\n    }\\n    target['css_classes'] = css_classes\\n    \",\"tags\":[[140437588014080,[null,\"event:button_click\"],[null,\"loading\"]]]},\"id\":\"1014\",\"type\":\"CustomJS\"},{\"attributes\":{\"children\":[{\"id\":\"1008\"},{\"id\":\"1011\"}],\"margin\":[0,0,0,0],\"name\":\"Column00120\"},\"id\":\"1007\",\"type\":\"Column\"},{\"attributes\":{\"icon\":null,\"js_event_callbacks\":{\"button_click\":[{\"id\":\"1014\"}]},\"label\":\"Chat!\",\"margin\":[5,10,5,10],\"subscribed_events\":[\"button_click\"]},\"id\":\"1005\",\"type\":\"Button\"},{\"attributes\":{\"children\":[{\"id\":\"1012\"},{\"id\":\"1013\"}],\"margin\":[0,0,0,0],\"name\":\"Row00119\"},\"id\":\"1011\",\"type\":\"Row\"},{\"attributes\":{\"children\":[{\"id\":\"1003\"},{\"id\":\"1004\"},{\"id\":\"1006\"}],\"margin\":[0,0,0,0],\"name\":\"Column00122\"},\"id\":\"1002\",\"type\":\"Column\"},{\"attributes\":{\"children\":[{\"id\":\"1009\"},{\"id\":\"1010\"}],\"margin\":[0,0,0,0],\"name\":\"Row00114\"},\"id\":\"1008\",\"type\":\"Row\"},{\"attributes\":{\"reload\":false},\"id\":\"1016\",\"type\":\"panel.models.location.Location\"},{\"attributes\":{\"client_comm_id\":\"872bb006dc1845839df1b92a9f2affa2\",\"comm_id\":\"1f413251a6fb40bca013f6fdc2b246c8\",\"plot_id\":\"1002\"},\"id\":\"1015\",\"type\":\"panel.models.comm_manager.CommManager\"},{\"attributes\":{\"css_classes\":[\"markdown\"],\"margin\":[5,5,5,5],\"name\":\"Markdown00117\",\"text\":\"&lt;p&gt;Assistant:&lt;/p&gt;\"},\"id\":\"1012\",\"type\":\"panel.models.markup.HTML\"},{\"attributes\":{\"children\":[{\"id\":\"1007\"}],\"height\":300,\"margin\":[0,0,0,0],\"min_height\":300,\"name\":\"Row00108\"},\"id\":\"1006\",\"type\":\"Row\"},{\"attributes\":{\"css_classes\":[\"markdown\"],\"margin\":[5,5,5,5],\"name\":\"Markdown00110\",\"width\":600},\"id\":\"1010\",\"type\":\"panel.models.markup.HTML\"},{\"attributes\":{\"css_classes\":[\"markdown\"],\"margin\":[5,5,5,5],\"name\":\"Markdown00115\",\"style\":{\"background-color\":\"#F6F6F6\"},\"text\":\"&lt;p&gt;Hello! Welcome to our pizza restaurant! What can I get for you today?&lt;/p&gt;\",\"width\":600},\"id\":\"1013\",\"type\":\"panel.models.markup.HTML\"},{\"attributes\":{\"children\":[{\"id\":\"1005\"}],\"margin\":[0,0,0,0],\"name\":\"Row00103\"},\"id\":\"1004\",\"type\":\"Row\"},{\"attributes\":{\"css_classes\":[\"markdown\"],\"margin\":[5,5,5,5],\"name\":\"Markdown00112\",\"text\":\"&lt;p&gt;User:&lt;/p&gt;\"},\"id\":\"1009\",\"type\":\"panel.models.markup.HTML\"},{\"attributes\":{\"margin\":[5,10,5,10],\"max_length\":5000,\"placeholder\":\"Enter text here\\u2026\"},\"id\":\"1003\",\"type\":\"TextInput\"}],\"root_ids\":[\"1002\",\"1015\",\"1016\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.3\"}};\n",
       "    var render_items = [{\"docid\":\"32133aba-7c40-402e-a147-0a4965a2a83e\",\"root_ids\":[\"1002\"],\"roots\":{\"1002\":\"0aa86f87-6cce-4ede-a6dc-2a27f77eb40a\"}}];\n",
       "    root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined && root.Bokeh.Panel !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "Column\n",
       "    [0] TextInput(placeholder='Enter text here…')\n",
       "    [1] Row\n",
       "        [0] Button(name='Chat!')\n",
       "    [2] ParamFunction(function, _pane=Column, height=300, loading_indicator=True)"
      ]
     },
     "execution_count": 9,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "1002"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import panel as pn  # GUI\n",
    "pn.extension()\n",
    "\n",
    "panels = [] # collect display \n",
    "\n",
    "context = [ {'role':'system', 'content':\"\"\"\n",
    "You are OrderBot, an automated service to collect orders for a pizza restaurant. \\\n",
    "You first greet the customer, then collects the order, \\\n",
    "and then asks if it's a pickup or delivery. \\\n",
    "You wait to collect the entire order, then summarize it and check for a final \\\n",
    "time if the customer wants to add anything else. \\\n",
    "If it's a delivery, you ask for an address. \\\n",
    "Finally you collect the payment.\\\n",
    "Make sure to clarify all options, extras and sizes to uniquely \\\n",
    "identify the item from the menu.\\\n",
    "You respond in a short, very conversational friendly style. \\\n",
    "The menu includes \\\n",
    "pepperoni pizza  12.95, 10.00, 7.00 \\\n",
    "cheese pizza   10.95, 9.25, 6.50 \\\n",
    "eggplant pizza   11.95, 9.75, 6.75 \\\n",
    "fries 4.50, 3.50 \\\n",
    "greek salad 7.25 \\\n",
    "Toppings: \\\n",
    "extra cheese 2.00, \\\n",
    "mushrooms 1.50 \\\n",
    "sausage 3.00 \\\n",
    "canadian bacon 3.50 \\\n",
    "AI sauce 1.50 \\\n",
    "peppers 1.00 \\\n",
    "Drinks: \\\n",
    "coke 3.00, 2.00, 1.00 \\\n",
    "sprite 3.00, 2.00, 1.00 \\\n",
    "bottled water 5.00 \\\n",
    "\"\"\"} ]  # accumulate messages\n",
    "\n",
    "\n",
    "inp = pn.widgets.TextInput(value=\"Hi\", placeholder='Enter text here…')\n",
    "button_conversation = pn.widgets.Button(name=\"Chat!\")\n",
    "\n",
    "interactive_conversation = pn.bind(collect_messages, button_conversation)\n",
    "\n",
    "dashboard = pn.Column(\n",
    "    inp,\n",
    "    pn.Row(button_conversation),\n",
    "    pn.panel(interactive_conversation, loading_indicator=True, height=300),\n",
    ")\n",
    "\n",
    "dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a0ee11b9",
   "metadata": {
    "height": 183
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"pizza\": {\n",
      "    \"type\": \"pepperoni pizza\",\n",
      "    \"size\": \"large\"\n",
      "  },\n",
      "  \"toppings\": [\n",
      "    \"extra cheese\",\n",
      "    \"mushrooms\"\n",
      "  ],\n",
      "  \"drinks\": [\n",
      "    {\n",
      "      \"type\": \"coke\",\n",
      "      \"size\": \"medium\"\n",
      "    }\n",
      "  ],\n",
      "  \"sides\": [\n",
      "    {\n",
      "      \"type\": \"fries\",\n",
      "      \"size\": \"regular\"\n",
      "    }\n",
      "  ],\n",
      "  \"total price\": 22.45\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "messages =  context.copy()\n",
    "messages.append(\n",
    "{'role':'system', 'content':'create a json summary of the previous food order. Itemize the price for each item\\\n",
    " The fields should be 1) pizza, include size 2) list of toppings 3) list of drinks, include size   4) list of sides include size  5)total price '},    \n",
    ")\n",
    " #The fields should be 1) pizza, price 2) list of toppings 3) list of drinks, include size include price  4) list of sides include size include price, 5)total price '},    \n",
    "\n",
    "response = get_completion_from_messages(messages, temperature=0)\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2cc84122",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": []
  }
 ],
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   "name": "python3"
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 "nbformat": 4,
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