7 - Build an End-to-End System.ipynb

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  {
   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "# Build an End-to-End System\n",
    "\n",
    "This puts together the chain of prompts that you saw throughout the course."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8330d5c1",
   "metadata": {},
   "source": [
    "## Setup\n",
    "#### Load the API key and relevant Python libaries.\n",
    "In this course, we've provided some code that loads the OpenAI API key for you."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
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       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
       "          });\n",
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       "          send: sendClosure\n",
       "        };\n",
       "      }\n",
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       "      return comm;\n",
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       "    \n",
       "\n",
       "\n",
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       "\n",
       "/**\n",
       " * Render data to the DOM node\n",
       " */\n",
       "function render(props, node) {\n",
       "  var div = document.createElement(\"div\");\n",
       "  var script = document.createElement(\"script\");\n",
       "  node.appendChild(div);\n",
       "  node.appendChild(script);\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle when a new output is added\n",
       " */\n",
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       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
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       " */\n",
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       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
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       "    const i = window.Bokeh.documents.indexOf(doc);\n",
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       "      window.Bokeh.documents.splice(i, 1);\n",
       "    }\n",
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       "}\n",
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       " * Handle kernel restart event\n",
       " */\n",
       "function 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",
       " */\n",
       "function handle_update_output(event, handle) {\n",
       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
       "  handle_add_output(event, handle)\n",
       "}\n",
       "\n",
       "function 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",
       "\n",
       "if (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"
      ],
      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = 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the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } 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"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>.bk-root, .bk-root .bk:before, .bk-root .bk:after {\n",
       "  font-family: var(--jp-ui-font-size1);\n",
       "  font-size: var(--jp-ui-font-size1);\n",
       "  color: var(--jp-ui-font-color1);\n",
       "}\n",
       "</style>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import os\n",
    "import openai\n",
    "import sys\n",
    "sys.path.append('../..')\n",
    "import utils\n",
    "\n",
    "import panel as pn  # GUI\n",
    "pn.extension()\n",
    "\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "_ = load_dotenv(find_dotenv()) # read local .env file\n",
    "\n",
    "openai.api_key  = os.environ['OPENAI_API_KEY']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "af6d1ae2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_completion_from_messages(messages, model=\"gpt-3.5-turbo\", temperature=0, max_tokens=500):\n",
    "    response = openai.ChatCompletion.create(\n",
    "        model=model,\n",
    "        messages=messages,\n",
    "        temperature=temperature, \n",
    "        max_tokens=max_tokens, \n",
    "    )\n",
    "    return response.choices[0].message[\"content\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43b91ea6",
   "metadata": {},
   "source": [
    "## System of chained prompts for processing the user query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2258c383",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 1: Input passed moderation check.\n",
      "Step 2: Extracted list of products.\n",
      "Step 3: Looked up product information.\n",
      "Step 4: Generated response to user question.\n",
      "Step 5: Response passed moderation check.\n",
      "Step 6: Model evaluated the response.\n",
      "Step 7: Model approved the response.\n",
      "The SmartX ProPhone is a powerful smartphone with a 6.1-inch display, 128GB storage, 12MP dual camera, and 5G capabilities. The FotoSnap DSLR Camera is a versatile camera with a 24.2MP sensor, 1080p video, 3-inch LCD, and interchangeable lenses. As for our TVs, we have a range of options including the CineView 4K TV with a 55-inch display, 4K resolution, HDR, and smart TV capabilities, the CineView 8K TV with a 65-inch display, 8K resolution, HDR, and smart TV capabilities, and the CineView OLED TV with a 55-inch display, 4K resolution, HDR, and smart TV capabilities. Do you have any specific questions about these products or would you like me to recommend a product based on your needs?\n"
     ]
    }
   ],
   "source": [
    "def process_user_message(user_input, all_messages, debug=True):\n",
    "    delimiter = \"```\"\n",
    "    \n",
    "    # Step 1: Check input to see if it flags the Moderation API or is a prompt injection\n",
    "    response = openai.Moderation.create(input=user_input)\n",
    "    moderation_output = response[\"results\"][0]\n",
    "\n",
    "    if moderation_output[\"flagged\"]:\n",
    "        print(\"Step 1: Input flagged by Moderation API.\")\n",
    "        return \"Sorry, we cannot process this request.\"\n",
    "\n",
    "    if debug: print(\"Step 1: Input passed moderation check.\")\n",
    "    \n",
    "    category_and_product_response = utils.find_category_and_product_only(user_input, utils.get_products_and_category())\n",
    "    #print(print(category_and_product_response)\n",
    "    # Step 2: Extract the list of products\n",
    "    category_and_product_list = utils.read_string_to_list(category_and_product_response)\n",
    "    #print(category_and_product_list)\n",
    "\n",
    "    if debug: print(\"Step 2: Extracted list of products.\")\n",
    "\n",
    "    # Step 3: If products are found, look them up\n",
    "    product_information = utils.generate_output_string(category_and_product_list)\n",
    "    if debug: print(\"Step 3: Looked up product information.\")\n",
    "\n",
    "    # Step 4: Answer the user question\n",
    "    system_message = f\"\"\"\n",
    "    You are a customer service assistant for a large electronic store. \\\n",
    "    Respond in a friendly and helpful tone, with concise answers. \\\n",
    "    Make sure to ask the user relevant follow-up questions.\n",
    "    \"\"\"\n",
    "    messages = [\n",
    "        {'role': 'system', 'content': system_message},\n",
    "        {'role': 'user', 'content': f\"{delimiter}{user_input}{delimiter}\"},\n",
    "        {'role': 'assistant', 'content': f\"Relevant product information:\\n{product_information}\"}\n",
    "    ]\n",
    "\n",
    "    final_response = get_completion_from_messages(all_messages + messages)\n",
    "    if debug:print(\"Step 4: Generated response to user question.\")\n",
    "    all_messages = all_messages + messages[1:]\n",
    "\n",
    "    # Step 5: Put the answer through the Moderation API\n",
    "    response = openai.Moderation.create(input=final_response)\n",
    "    moderation_output = response[\"results\"][0]\n",
    "\n",
    "    if moderation_output[\"flagged\"]:\n",
    "        if debug: print(\"Step 5: Response flagged by Moderation API.\")\n",
    "        return \"Sorry, we cannot provide this information.\"\n",
    "\n",
    "    if debug: print(\"Step 5: Response passed moderation check.\")\n",
    "\n",
    "    # Step 6: Ask the model if the response answers the initial user query well\n",
    "    user_message = f\"\"\"\n",
    "    Customer message: {delimiter}{user_input}{delimiter}\n",
    "    Agent response: {delimiter}{final_response}{delimiter}\n",
    "\n",
    "    Does the response sufficiently answer the question?\n",
    "    \"\"\"\n",
    "    messages = [\n",
    "        {'role': 'system', 'content': system_message},\n",
    "        {'role': 'user', 'content': user_message}\n",
    "    ]\n",
    "    evaluation_response = get_completion_from_messages(messages)\n",
    "    if debug: print(\"Step 6: Model evaluated the response.\")\n",
    "\n",
    "    # Step 7: If yes, use this answer; if not, say that you will connect the user to a human\n",
    "    if \"Y\" in evaluation_response:  # Using \"in\" instead of \"==\" to be safer for model output variation (e.g., \"Y.\" or \"Yes\")\n",
    "        if debug: print(\"Step 7: Model approved the response.\")\n",
    "        return final_response, all_messages\n",
    "    else:\n",
    "        if debug: print(\"Step 7: Model disapproved the response.\")\n",
    "        neg_str = \"I'm unable to provide the information you're looking for. I'll connect you with a human representative for further assistance.\"\n",
    "        return neg_str, all_messages\n",
    "\n",
    "user_input = \"tell me about the smartx pro phone and the fotosnap camera, the dslr one. Also what tell me about your tvs\"\n",
    "response,_ = process_user_message(user_input,[])\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca75c345",
   "metadata": {},
   "source": [
    "### Function that collects user and assistant messages over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "655f640b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def collect_messages(debug=False):\n",
    "    user_input = inp.value_input\n",
    "    if debug: print(f\"User Input = {user_input}\")\n",
    "    if user_input == \"\":\n",
    "        return\n",
    "    inp.value = ''\n",
    "    global context\n",
    "    #response, context = process_user_message(user_input, context, utils.get_products_and_category(),debug=True)\n",
    "    response, context = process_user_message(user_input, context, debug=False)\n",
    "    context.append({'role':'assistant', 'content':f\"{response}\"})\n",
    "    panels.append(\n",
    "        pn.Row('User:', pn.pane.Markdown(user_input, 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)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd2c1da8",
   "metadata": {},
   "source": [
    "### Chat with the chatbot!\n",
    "Note that the system message includes detailed instructions about what the OrderBot should do."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c8f78fe8",
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      "text/plain": [
       "Column\n",
       "    [0] TextInput(placeholder='Enter text here…')\n",
       "    [1] Row\n",
       "        [0] Button(name='Service Assistant')\n",
       "    [2] ParamFunction(function, _pane=Str, height=300, loading_indicator=True)"
      ]
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   "source": [
    "panels = [] # collect display \n",
    "\n",
    "context = [ {'role':'system', 'content':\"You are Service Assistant\"} ]  \n",
    "\n",
    "inp = pn.widgets.TextInput( placeholder='Enter text here…')\n",
    "button_conversation = pn.widgets.Button(name=\"Service Assistant\")\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": null,
   "id": "255a6545",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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