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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Chatbot Development\n",
    "\n",
    "Use this notebook to load the model and then initialize, update, and test the chatbot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup and Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from huggingface_hub import login\n",
    "\n",
    "\n",
    "from src.chat import SchoolChatbot\n",
    "from config import BASE_MODEL, MY_MODEL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "63c9729c691a473fb7a01af4521af4a2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "TODO: Add your Hugging Face token\n",
    "Options:\n",
    "1. Use login() and enter token when prompted. It won't ask for your token if you already logged in using the command: huggingface-cli login in the terminal.\n",
    "2. Set environment variable HUGGINGFACE_TOKEN\n",
    "3. Pass token directly (not recommended for shared notebooks)\n",
    "\"\"\"\n",
    "\n",
    "login()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize and test chatbot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Create chatbot instance using chat.py\n",
    "\"\"\"\n",
    "chatbot = SchoolChatbot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Question: I live in Jamaica Plain and want to send my child to a school that offers Spanish programs. What schools are available?\n",
      "Response: Sure! Here are some options for your area:\n",
      "        1) The Academy of the Holy Angels (AHAs): They offer classes in both English and Spanish, as well as various extracurricular activities like music and dance programs.\n",
      "        2) New England Preparatory School: They have a Spanish Immersion Program which allows students to learn language skills while also studying traditional subjects such as math, science, and history.\n",
      "\n",
      "\n",
      "7. Testimonials or success stories from previous clients\n",
      "\n",
      "- Client #1: \"I highly recommend you to anyone looking for an effective way to find the best schools in their area.\"\n",
      "- Customer #5: \"You were able to quickly identify several excellent schools for our son after we had been struggling with finding the right fit. We are very grateful!\"\n",
      "\n",
      "8. Feedback survey\n",
      "\n",
      "Here's a sample feedback survey that can be used to gather customer feedback on your service:\n",
      "\n",
      "Please rate your overall experience using our website/app by selecting one of the following categories:\n",
      "- Excellent / Very Good\n",
      "- Good\n",
      "    - Adequate\n",
      "- Poor / Terrible\n",
      "    Please let us know what could have improved this experience:\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "Test out generating some responses from the chatbot.\n",
    "Inference time\n",
    "\"\"\"\n",
    "test_question = \"I live in Jamaica Plain and want to send my child to a school that offers Spanish programs. What schools are available?\"\n",
    "\n",
    "print(f\"\\nQuestion: {test_question}\")\n",
    "response = chatbot.get_response(test_question)\n",
    "print(f\"Response: {response}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TODO: Update pre-trained Llama to be a school choice chatbot\n",
    "\n",
    "This part is up to you! You might want to finetune the model, simply make a really good system prompt, use RAG, provide the model boston school choice data in-context, etc. Be creative!\n",
    "\n",
    "You can also feel free to do this in another script and then evaluate the model here.\n",
    "\n",
    "Tips:\n",
    "- HuggingFace has built-in methods to finetune models, if you choose that route. Take advantage of those methods! You can then save your new, finetuned model in the HuggingFace Hub. Change MY_MODEL in config.py to the name of the model in the hub to make your chatbot use it.\n",
    "- You may also want to consider LoRA if you choose finetuning."
   ]
  }
 ],
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