{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cc0d8e5d80814f7999931be255d575af",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Generating train split: 0 examples [00:00, ? examples/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from datasets import load_dataset\n",
    "dataset = load_dataset('csv', data_files='../data/raw/customer_support.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatasetDict({\n",
       "    train: Dataset({\n",
       "        features: ['instruction', 'response'],\n",
       "        num_rows: 26872\n",
       "    })\n",
       "})"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "data": {
      "text/plain": [
       "2472"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "res = [len(i) for i in dataset['train']['response']]\n",
    "print(res)\n",
    "np.max(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"I can sense that you're seeking assistance with canceling your purchase with the purchase number {{Order Number}}. I apologize for any inconvenience caused, and I'm here to guide you through the process.\\n\\nTo cancel your purchase, please follow these steps:\\n\\n1. Log into your account: Visit our {{Online Company Portal Info}} and sign in using your credentials.\\n2. Locate your order: Once logged in, navigate to the '{{Online Order Interaction}}' or '{{Online Order Interaction}}' section to find the purchase with the order number {{Order Number}}.\\n3. Initiate the cancellation: Upon finding your purchase, look for the option labeled '{{Online Order Interaction}}' and click on it to initiate the cancellation process.\\n4. Confirm the cancellation: Our system might ask for confirmation or feedback regarding the cancellation. Kindly provide the necessary information to complete the process.\\n5. Seek additional support: If you encounter any difficulties or require further assistance, our dedicated customer support team is available during {{Customer Support Hours}}. You can contact us at {{Customer Support Phone Number}} or use the Live Chat feature on our {{Website URL}}.\\n\\nWe appreciate your understanding and value your satisfaction. Should you have any more questions or concerns, feel free to reach out to us. We're here to help you.\""
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset['train']['response'][2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "split_dataset = dataset['train'].train_test_split(test_size=0.2, seed=42)\n",
    "\n",
    "# Rename the test split to val for clarity\n",
    "train_dataset = split_dataset['train']\n",
    "val_dataset = split_dataset['test']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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