chatbot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import boto3\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!wget https://download.microsoft.com/download/A/A/9/AA9C9802-B448-4361-89E0-DBF24D5A5C2C/WikiQACodePackage.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!unzip WikiQACodePackage.zip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "def create_faq_format(inpath):\n",
    "    faq_list = []\n",
    "    \n",
    "    with open(inpath) as f:\n",
    "        lines = [line.strip('\\n') for line in f]\n",
    "    for i in range(2, len(lines)):\n",
    "        l = lines[i].split('\\t')\n",
    "        if l[2]==\"1\":\n",
    "            faq_list.append({\"Question\":l[0],\"Answer\":l[1]})\n",
    "                \n",
    "    return faq_list\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "qa_list = create_faq_format(\"WikiQACodePackage/data/wiki/WikiQASent-train.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(qa_list, columns=[\"Question\",\"Answer\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop_duplicates(subset='Question', keep=\"first\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv('faq.csv', index=False) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s3 = boto3.resource('s3')\n",
    "s3.meta.client.upload_file(\"faq.csv\", 'my-kendra-index', 'faq/faq.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "kendra = boto3.client('kendra')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_answer(text):\n",
    "    response = client.kendra(\n",
    "            IndexId='4a08fb37-xxxx-4941-bea0-xxxxxx',\n",
    "            QueryText=text,\n",
    "            QueryResultTypeFilter='QUESTION_ANSWER'\n",
    "    )\n",
    "    return response\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "get_answer(\"how long was angelina on the jersey shore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_pytorch_p36",
   "language": "python",
   "name": "conda_pytorch_p36"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}