00-playground/48-building-systems-chatgpt-api/L2_student.ipynb

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   "source": [
    "# L2: Evaluate Inputs: Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26fd0696-18e6-4029-8738-fecba92851db",
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   "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,
   "id": "87f647e2",
   "metadata": {
    "height": 115
   },
   "outputs": [],
   "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.environ['OPENAI_API_KEY']"
   ]
  },
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   "id": "101624a2",
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    "height": 200
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   "source": [
    "def get_completion_from_messages(messages, \n",
    "                                 model=\"gpt-3.5-turbo\", \n",
    "                                 temperature=0, \n",
    "                                 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": "d3db09d1-6253-4c9e-9ad1-5a6134df3e6c",
   "metadata": {},
   "source": [
    "#### Classify customer queries to handle different cases"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8db30f42",
   "metadata": {
    "height": 812
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"primary\": \"Account Management\",\n",
      "  \"secondary\": \"Close account\"\n",
      "}  \n",
      "\n"
     ]
    }
   ],
   "source": [
    "delimiter = \"####\"\n",
    "system_message = f\"\"\"\n",
    "You will be provided with customer service queries. \\\n",
    "The customer service query will be delimited with \\\n",
    "{delimiter} characters.\n",
    "Classify each query into a primary category \\\n",
    "and a secondary category. \n",
    "Provide your output in json format with the \\\n",
    "keys: primary and secondary.\n",
    "\n",
    "Primary categories: Billing, Technical Support, \\\n",
    "Account Management, or General Inquiry.\n",
    "\n",
    "Billing secondary categories:\n",
    "Unsubscribe or upgrade\n",
    "Add a payment method\n",
    "Explanation for charge\n",
    "Dispute a charge\n",
    "\n",
    "Technical Support secondary categories:\n",
    "General troubleshooting\n",
    "Device compatibility\n",
    "Software updates\n",
    "\n",
    "Account Management secondary categories:\n",
    "Password reset\n",
    "Update personal information\n",
    "Close account\n",
    "Account security\n",
    "\n",
    "General Inquiry secondary categories:\n",
    "Product information\n",
    "Pricing\n",
    "Feedback\n",
    "Speak to a human\n",
    "\n",
    "\"\"\"\n",
    "user_message = f\"\"\"\\\n",
    "I want you to delete my profile and all of my user data\"\"\"\n",
    "messages =  [  \n",
    "{'role':'system', \n",
    " 'content': system_message},    \n",
    "{'role':'user', \n",
    " 'content': f\"{delimiter}{user_message}{delimiter}\"},  \n",
    "] \n",
    "response = get_completion_from_messages(messages)\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f9a5a790",
   "metadata": {
    "height": 183
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"primary\": \"General Inquiry\",\n",
      "  \"secondary\": \"Product information\"\n",
      "}  \n",
      "\n"
     ]
    }
   ],
   "source": [
    "user_message = f\"\"\"\\\n",
    "Tell me more about your flat screen tvs\"\"\"\n",
    "messages =  [  \n",
    "{'role':'system', \n",
    " 'content': system_message},    \n",
    "{'role':'user', \n",
    " 'content': f\"{delimiter}{user_message}{delimiter}\"},  \n",
    "] \n",
    "response = get_completion_from_messages(messages)\n",
    "print(response)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5cfd2fae",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": []
  }
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