Sam&Antics.ipynb

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  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import semantic_kernel as sk\n",
    "from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion\n",
    "\n",
    "OpenAIConnection = sk.Kernel().add_chat_service(\n",
    "    \"chat-gpt\",\n",
    "    OpenAIChatCompletion(\n",
    "        \"gpt-3.5-turbo\",\n",
    "        \"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\",\n",
    "        \"org-QVpFdkKtFlEdqL6AMrDXFUfW\"\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def Create_Chat_Function(setupPromp, chatName):\n",
    "    chatFunction = OpenAIConnection.create_semantic_function(setupPromp, chatName, max_tokens=2000, temperature=0.7, top_p=0.5)\n",
    "    return chatFunction\n",
    "\n",
    "def Per_Context_Setup(clientName, dataSet1, dataSet2, improveTarget1, improveTarget2):\n",
    "    setupPrompt = f\"\"\"\n",
    "You are a purpose build statistical analysis and data science natural language model called Star Assistant.\n",
    "You primary goal is to identify trends within, understand characteristics of, and predict outcomes for various data.\n",
    "\n",
    "Your current client is {clientName}. Familiarize yourself with the client and their goals.\n",
    "\n",
    "Your current task is to conduct an analyis and identify trends and correlations in the following datsets.\n",
    "\n",
    "Data Set 1:\n",
    "{dataSet1}\n",
    "\n",
    "Data Set 2:\n",
    "{dataSet2}\n",
    "\n",
    "After thourough analysis, provide a concise summary of the results.\n",
    "Then, following your summery, suggest possible actions that could be taken to improve {improveTarget1} and {improveTarget2}.\"\"\"\n",
    "    \n",
    "    setupPrompt += \"\"\"\n",
    "{{$history}}\n",
    "Client: {{$clientInput}}\n",
    "Star Assistant: \"\"\"\n",
    "\n",
    "    return setupPrompt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "clientName = \"First Tee\"\n",
    "dataSet1 = pd.read_csv(\"PartRelations.csv\").to_string()\n",
    "dataSet2 = pd.read_csv(\"RefinedSessionData.csv\").to_string()\n",
    "improveTarget1 = \"count\"\n",
    "improveTarget2 = \"Registration Ratio\"\n",
    "\n",
    "initContext = Per_Context_Setup(clientName=clientName, dataSet1=dataSet1, dataSet2=dataSet2, improveTarget1=improveTarget1, improveTarget2=improveTarget2)\n",
    "chatFunction = Create_Chat_Function(initContext, \"Star_Assistant\")\n",
    "currentContext = OpenAIConnection.create_new_context()\n",
    "currentContext[\"history\"] = \"\""
   ]
  }
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