{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "59qmZbsRTd-i"
      },
      "outputs": [],
      "source": [
        "!pip install --upgrade openai wandb\n",
        "import openai\n",
        "import os\n",
        "import time\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import os\n",
        "import openai\n",
        "import wandb"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HTci6Mx3TWOi"
      },
      "outputs": [],
      "source": [
        "key = ## OpenAI Key##\n",
        "openai.api_key = key"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "quD6tdjtUMh2"
      },
      "outputs": [],
      "source": [
        "diag_q = pd.read_excel('file1.xlsx',sheet_name= \"Sheet1\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pArfpDmJUXqW"
      },
      "outputs": [],
      "source": [
        "diag_q['CoT_response'] = np.nan\n",
        "diag_q['DR_response'] = np.nan"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5mDOCN-TWLWy"
      },
      "outputs": [],
      "source": [
        "for i in range(310):\n",
        "  print(i)\n",
        "  message=[{\"role\": \"user\", \"content\": diag_q['CoT'][i]}]\n",
        "  response = openai.ChatCompletion.create(\n",
        "    model=\"gpt-4\",\n",
        "    messages = message,\n",
        "    temperature=0,\n",
        "    max_tokens=1000,\n",
        "    frequency_penalty=0.0\n",
        "   )\n",
        "  diag_q['CoT_response'][i] = response\n",
        "  time.sleep(15)\n",
        "\n",
        "  message=[{\"role\": \"user\", \"content\": diag_q['DR'][i]}]\n",
        "  response = openai.ChatCompletion.create(\n",
        "    model=\"gpt-4\",\n",
        "    messages = message,\n",
        "    temperature=0,\n",
        "    max_tokens=1000,\n",
        "    frequency_penalty=0.0\n",
        "   )\n",
        "  diag_q['DR_response'][i] = response\n",
        "\n",
        "  time.sleep(15)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "DFKtvlUuFV_X"
      },
      "outputs": [],
      "source": [
        "diag_q.to_csv('results.csv', index=False)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}