diff --git a/content/LangChain for LLM Application Development/Untitled.ipynb b/content/LangChain for LLM Application Development/Untitled.ipynb
deleted file mode 100644
index 4dd6a76..0000000
--- a/content/LangChain for LLM Application Development/Untitled.ipynb	
+++ /dev/null
@@ -1,424 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "51e47840",
-   "metadata": {},
-   "source": [
-    "# 第四章 基于LangChain的文档问答\n",
-    "本章内容主要利用langchain构建向量数据库，可以在文档上方或关于文档回答问题，因此，给定从PDF文件、网页或某些公司的内部文档收集中提取的文本，使用llm回答有关这些文档内容的问题"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "ef807f79",
-   "metadata": {},
-   "source": [
-    "## 一、环境配置\n",
-    "\n",
-    "安装langchain，设置chatGPT的OPENAI_API_KEY\n",
-    "* 安装langchain\n",
-    "```\n",
-    "pip install --upgrade langchain\n",
-    "```\n",
-    "* 安装docarray\n",
-    "```\n",
-    "pip install docarray\n",
-    "```\n",
-    "* 设置API-KEY环境变量\n",
-    "```\n",
-    "export OPENAI_API_KEY='api-key'\n",
-    "\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "af3ffa97",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "\n",
-    "from dotenv import load_dotenv, find_dotenv\n",
-    "_ = load_dotenv(find_dotenv()) # 读取系统中的环境变量"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "49081091",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "False"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "load_dotenv(find_dotenv())\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "3bcb095f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import os\n",
-    "os.environ[\"OPENAI_API_KEY\"] = \"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\"\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "46595e8c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#导入检索QA链，在文档上进行检索\n",
-    "from langchain.chains import RetrievalQA\n",
-    "from langchain.chat_models import ChatOpenAI\n",
-    "from langchain.document_loaders import CSVLoader\n",
-    "from langchain.vectorstores import DocArrayInMemorySearch\n",
-    "from IPython.display import display, Markdown"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "e511efa5",
-   "metadata": {},
-   "source": [
-    "## 使用 LangChain 完成一次问答"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "3ab4b9d1",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'\\n\\n人工智能是一种重要的现代科技，它可以大大改善人类生活，减轻人类负担，提升工作效率。它可以帮助人们提高生产力，更有效地管理组织，并且可以提供更为准确的数据，帮助人们更好地决策。另外，人工智能可以帮助科学家发现新的药物，改善医疗服务，以及发展新的环保技术。总之，人工智能是一项重要的科技，具有广泛的应用前景。'"
-      ]
-     },
-     "execution_count": 13,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from langchain.llms import OpenAI\n",
-    "\n",
-    "llm = OpenAI(model_name=\"text-davinci-003\",max_tokens=1024)\n",
-    "llm(\"怎么评价人工智能\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "884399f1",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "file = 'OutdoorClothingCatalog_1000.csv'\n",
-    "loader = CSVLoader(file_path=file)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "52ec965a",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>0</th>\n",
-       "      <th>1</th>\n",
-       "      <th>2</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>NaN</td>\n",
-       "      <td>name</td>\n",
-       "      <td>description</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Women's Campside Oxfords</td>\n",
-       "      <td>This ultracomfortable lace-to-toe Oxford boast...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>1.0</td>\n",
-       "      <td>Recycled Waterhog Dog Mat, Chevron Weave</td>\n",
-       "      <td>Protect your floors from spills and splashing ...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>2.0</td>\n",
-       "      <td>Infant and Toddler Girls' Coastal Chill Swimsu...</td>\n",
-       "      <td>She'll love the bright colors, ruffles and exc...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>3.0</td>\n",
-       "      <td>Refresh Swimwear, V-Neck Tankini Contrasts</td>\n",
-       "      <td>Whether you're going for a swim or heading out...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>996</th>\n",
-       "      <td>995.0</td>\n",
-       "      <td>Men's  Classic Denim, Standard Fit</td>\n",
-       "      <td>Crafted from premium denim that will last wash...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>997</th>\n",
-       "      <td>996.0</td>\n",
-       "      <td>CozyPrint Sweater Fleece Pullover</td>\n",
-       "      <td>The ultimate sweater fleece - made from superi...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>998</th>\n",
-       "      <td>997.0</td>\n",
-       "      <td>Women's NRS Endurance Spray Paddling Pants</td>\n",
-       "      <td>These comfortable and affordable splash paddli...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>999</th>\n",
-       "      <td>998.0</td>\n",
-       "      <td>Women's Stop Flies Hoodie</td>\n",
-       "      <td>This great-looking hoodie uses No Fly Zone Tec...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1000</th>\n",
-       "      <td>999.0</td>\n",
-       "      <td>Modern Utility Bag</td>\n",
-       "      <td>This US-made crossbody bag is built with the s...</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>1001 rows × 3 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          0                                                  1  \\\n",
-       "0       NaN                                               name   \n",
-       "1       0.0                           Women's Campside Oxfords   \n",
-       "2       1.0           Recycled Waterhog Dog Mat, Chevron Weave   \n",
-       "3       2.0  Infant and Toddler Girls' Coastal Chill Swimsu...   \n",
-       "4       3.0         Refresh Swimwear, V-Neck Tankini Contrasts   \n",
-       "...     ...                                                ...   \n",
-       "996   995.0                 Men's  Classic Denim, Standard Fit   \n",
-       "997   996.0                  CozyPrint Sweater Fleece Pullover   \n",
-       "998   997.0         Women's NRS Endurance Spray Paddling Pants   \n",
-       "999   998.0                          Women's Stop Flies Hoodie   \n",
-       "1000  999.0                                 Modern Utility Bag   \n",
-       "\n",
-       "                                                      2  \n",
-       "0                                           description  \n",
-       "1     This ultracomfortable lace-to-toe Oxford boast...  \n",
-       "2     Protect your floors from spills and splashing ...  \n",
-       "3     She'll love the bright colors, ruffles and exc...  \n",
-       "4     Whether you're going for a swim or heading out...  \n",
-       "...                                                 ...  \n",
-       "996   Crafted from premium denim that will last wash...  \n",
-       "997   The ultimate sweater fleece - made from superi...  \n",
-       "998   These comfortable and affordable splash paddli...  \n",
-       "999   This great-looking hoodie uses No Fly Zone Tec...  \n",
-       "1000  This US-made crossbody bag is built with the s...  \n",
-       "\n",
-       "[1001 rows x 3 columns]"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import pandas as pd\n",
-    "file = 'OutdoorClothingCatalog_1000.csv'\n",
-    "\n",
-    "data = pd.read_csv(file,header=None)\n",
-    "data"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "id": "efc6c592",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain.indexes import VectorstoreIndexCreator"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "5e90139b",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31mCanceled future for execute_request message before replies were done"
-     ]
-    },
-    {
-     "ename": "",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m在当前单元格或上一个单元格中执行代码时 Kernel 崩溃。请查看单元格中的代码，以确定故障的可能原因。有关详细信息，请单击 <a href='https://aka.ms/vscodeJupyterKernelCrash'>此处</a>。有关更多详细信息，请查看 Jupyter <a href='command:jupyter.viewOutput'>log</a>。"
-     ]
-    }
-   ],
-   "source": [
-    "index = VectorstoreIndexCreator(\n",
-    "    vectorstore_cls=DocArrayInMemorySearch\n",
-    ").from_loaders([loader])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "8249a523",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31mCanceled future for execute_request message before replies were done"
-     ]
-    },
-    {
-     "ename": "",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m在当前单元格或上一个单元格中执行代码时 Kernel 崩溃。请查看单元格中的代码，以确定故障的可能原因。有关详细信息，请单击 <a href='https://aka.ms/vscodeJupyterKernelCrash'>此处</a>。有关更多详细信息，请查看 Jupyter <a href='command:jupyter.viewOutput'>log</a>。"
-     ]
-    }
-   ],
-   "source": [
-    "from docarray import DocumentArray\n",
-    "\n",
-    "\n",
-    "\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "3b160609",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "query =\"Please list all your shirts with sun protection \\\n",
-    "in a table in markdown and summarize each one.\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "cf61d864",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "NameError",
-     "evalue": "name 'index' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m response \u001b[38;5;241m=\u001b[39m \u001b[43mindex\u001b[49m\u001b[38;5;241m.\u001b[39mquery(query)\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'index' is not defined"
-     ]
-    }
-   ],
-   "source": [
-    "response = index.query(query)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "0737f809",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "display(Markdown(response))"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "chatGPT",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.16"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "4d8dc73ac51fd938ce7dec941fbf542c26232b3529b0c2a6ebc607bfa3d5aa69"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/content/LangChain for LLM Application Development/summary.ipynb b/content/LangChain for LLM Application Development/summary.ipynb
deleted file mode 100644
index c8cf285..0000000
--- a/content/LangChain for LLM Application Development/summary.ipynb	
+++ /dev/null
@@ -1,380 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "e1ce673f",
-   "metadata": {},
-   "source": [
-    "# Summarize"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "abbc4934",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import openai\n",
-    "import os\n",
-    "\n",
-    "from dotenv import load_dotenv, find_dotenv\n",
-    "_ = load_dotenv(find_dotenv()) # read local .env file\n",
-    "\n",
-    "openai.api_key  = os.getenv('OPENAI_API_KEY')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "19f13be6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def get_completion(prompt, model=\"gpt-3.5-turbo\"): # Andrew mentioned that the prompt/ completion paradigm is preferable for this class\n",
-    "    messages = [{\"role\": \"user\", \"content\": prompt}]\n",
-    "    response = openai.ChatCompletion.create(\n",
-    "        model=model,\n",
-    "        messages=messages,\n",
-    "        temperature=0, # this is the degree of randomness of the model's output\n",
-    "    )\n",
-    "    return response.choices[0].message[\"content\"]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a9a77385",
-   "metadata": {},
-   "source": [
-    "## 对文本做总结"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "37f412b5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "prod_review = \"\"\"\n",
-    "Got this panda plush toy for my daughter's birthday, \\\n",
-    "who loves it and takes it everywhere. It's soft and \\ \n",
-    "super cute, and its face has a friendly look. It's \\ \n",
-    "a bit small for what I paid though. I think there \\ \n",
-    "might be other options that are bigger for the \\ \n",
-    "same price. It arrived a day earlier than expected, \\ \n",
-    "so I got to play with it myself before I gave it \\ \n",
-    "to her.\n",
-    "\"\"\""
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "13d70836",
-   "metadata": {},
-   "source": [
-    "## 以单词/句子/字符限制进行总结"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "10c0c7e8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Soft and cute panda plush toy loved by daughter, but a bit small for the price. Arrived early.\n"
-     ]
-    }
-   ],
-   "source": [
-    "prompt = f\"\"\"\n",
-    "Your task is to generate a short summary of a product \\\n",
-    "review from an ecommerce site. \n",
-    "\n",
-    "Summarize the review below, delimited by triple \n",
-    "backticks, in at most 30 words. \n",
-    "\n",
-    "Review: ```{prod_review}```\n",
-    "\"\"\"\n",
-    "\n",
-    "response = get_completion(prompt)\n",
-    "print(response)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "64da0bc6",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The panda plush toy arrived a day earlier than expected, but the customer felt it was a bit small for the price paid.\n"
-     ]
-    }
-   ],
-   "source": [
-    "prompt = f\"\"\"\n",
-    "Your task is to generate a short summary of a product \\\n",
-    "review from an ecommerce site to give feedback to the \\\n",
-    "Shipping deparmtment. \n",
-    "\n",
-    "Summarize the review below, delimited by triple \n",
-    "backticks, in at most 30 words, and focusing on any aspects \\\n",
-    "that mention shipping and delivery of the product. \n",
-    "\n",
-    "Review: ```{prod_review}```\n",
-    "\"\"\"\n",
-    "\n",
-    "response = get_completion(prompt)\n",
-    "print(response)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "4e9f7803",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The panda plush toy is soft, cute, and loved by the recipient, but the price may be too high for its size.\n"
-     ]
-    }
-   ],
-   "source": [
-    "prompt = f\"\"\"\n",
-    "Your task is to generate a short summary of a product \\\n",
-    "review from an ecommerce site to give feedback to the \\\n",
-    "pricing deparmtment, responsible for determining the \\\n",
-    "price of the product.  \n",
-    "\n",
-    "Summarize the review below, delimited by triple \n",
-    "backticks, in at most 30 words, and focusing on any aspects \\\n",
-    "that are relevant to the price and perceived value. \n",
-    "\n",
-    "Review: ```{prod_review}```\n",
-    "\"\"\"\n",
-    "\n",
-    "response = get_completion(prompt)\n",
-    "print(response)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b6ed513e",
-   "metadata": {},
-   "source": [
-    "## 使用提取代替总结"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "a2035734",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The product arrived a day earlier than expected.\n"
-     ]
-    }
-   ],
-   "source": [
-    "prompt = f\"\"\"\n",
-    "Your task is to extract relevant information from \\ \n",
-    "a product review from an ecommerce site to give \\\n",
-    "feedback to the Shipping department. \n",
-    "\n",
-    "From the review below, delimited by triple quotes \\\n",
-    "extract the information relevant to shipping and \\ \n",
-    "delivery. Limit to 30 words. \n",
-    "\n",
-    "Review: ```{prod_review}```\n",
-    "\"\"\"\n",
-    "\n",
-    "response = get_completion(prompt)\n",
-    "print(response)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "32e0345b",
-   "metadata": {},
-   "source": [
-    "## 对多个文本做总结"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "f2d9dd87",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "review_1 = prod_review \n",
-    "\n",
-    "# review for a standing lamp\n",
-    "review_2 = \"\"\"\n",
-    "Needed a nice lamp for my bedroom, and this one \\\n",
-    "had additional storage and not too high of a price \\\n",
-    "point. Got it fast - arrived in 2 days. The string \\\n",
-    "to the lamp broke during the transit and the company \\\n",
-    "happily sent over a new one. Came within a few days \\\n",
-    "as well. It was easy to put together. Then I had a \\\n",
-    "missing part, so I contacted their support and they \\\n",
-    "very quickly got me the missing piece! Seems to me \\\n",
-    "to be a great company that cares about their customers \\\n",
-    "and products. \n",
-    "\"\"\"\n",
-    "\n",
-    "# review for an electric toothbrush\n",
-    "review_3 = \"\"\"\n",
-    "My dental hygienist recommended an electric toothbrush, \\\n",
-    "which is why I got this. The battery life seems to be \\\n",
-    "pretty impressive so far. After initial charging and \\\n",
-    "leaving the charger plugged in for the first week to \\\n",
-    "condition the battery, I've unplugged the charger and \\\n",
-    "been using it for twice daily brushing for the last \\\n",
-    "3 weeks all on the same charge. But the toothbrush head \\\n",
-    "is too small. I’ve seen baby toothbrushes bigger than \\\n",
-    "this one. I wish the head was bigger with different \\\n",
-    "length bristles to get between teeth better because \\\n",
-    "this one doesn’t.  Overall if you can get this one \\\n",
-    "around the $50 mark, it's a good deal. The manufactuer's \\\n",
-    "replacements heads are pretty expensive, but you can \\\n",
-    "get generic ones that're more reasonably priced. This \\\n",
-    "toothbrush makes me feel like I've been to the dentist \\\n",
-    "every day. My teeth feel sparkly clean! \n",
-    "\"\"\"\n",
-    "\n",
-    "# review for a blender\n",
-    "review_4 = \"\"\"\n",
-    "So, they still had the 17 piece system on seasonal \\\n",
-    "sale for around $49 in the month of November, about \\\n",
-    "half off, but for some reason (call it price gouging) \\\n",
-    "around the second week of December the prices all went \\\n",
-    "up to about anywhere from between $70-$89 for the same \\\n",
-    "system. And the 11 piece system went up around $10 or \\\n",
-    "so in price also from the earlier sale price of $29. \\\n",
-    "So it looks okay, but if you look at the base, the part \\\n",
-    "where the blade locks into place doesn’t look as good \\\n",
-    "as in previous editions from a few years ago, but I \\\n",
-    "plan to be very gentle with it (example, I crush \\\n",
-    "very hard items like beans, ice, rice, etc. in the \\ \n",
-    "blender first then pulverize them in the serving size \\\n",
-    "I want in the blender then switch to the whipping \\\n",
-    "blade for a finer flour, and use the cross cutting blade \\\n",
-    "first when making smoothies, then use the flat blade \\\n",
-    "if I need them finer/less pulpy). Special tip when making \\\n",
-    "smoothies, finely cut and freeze the fruits and \\\n",
-    "vegetables (if using spinach-lightly stew soften the \\ \n",
-    "spinach then freeze until ready for use-and if making \\\n",
-    "sorbet, use a small to medium sized food processor) \\ \n",
-    "that you plan to use that way you can avoid adding so \\\n",
-    "much ice if at all-when making your smoothie. \\\n",
-    "After about a year, the motor was making a funny noise. \\\n",
-    "I called customer service but the warranty expired \\\n",
-    "already, so I had to buy another one. FYI: The overall \\\n",
-    "quality has gone done in these types of products, so \\\n",
-    "they are kind of counting on brand recognition and \\\n",
-    "consumer loyalty to maintain sales. Got it in about \\\n",
-    "two days.\n",
-    "\"\"\"\n",
-    "\n",
-    "reviews = [review_1, review_2, review_3, review_4]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "43d84e1f",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0 Soft and cute panda plush toy loved by daughter, but a bit small for the price. Arrived early. \n",
-      "\n",
-      "1 Affordable lamp with storage, fast shipping, and excellent customer service. Easy to assemble and missing parts were quickly replaced. \n",
-      "\n",
-      "2 Good battery life, small toothbrush head, but effective cleaning. Good deal if bought around $50. \n",
-      "\n"
-     ]
-    },
-    {
-     "ename": "RateLimitError",
-     "evalue": "Rate limit reached for default-gpt-3.5-turbo in organization org-SoADSeM578ReGFBjktovCGZG on requests per min. Limit: 3 / min. Please try again in 20s. Contact us through our help center at help.openai.com if you continue to have issues. Please add a payment method to your account to increase your rate limit. Visit https://platform.openai.com/account/billing to add a payment method.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mRateLimitError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[12], line 12\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(reviews)):\n\u001b[1;32m      2\u001b[0m     prompt \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\"\"\u001b[39m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;124m    Your task is to generate a short summary of a product \u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124m \u001b[39m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;124m    review from an ecommerce site. \u001b[39m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;124m    Review: ```\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mreviews[i]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m```\u001b[39m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;124m    \u001b[39m\u001b[38;5;124m\"\"\"\u001b[39m\n\u001b[0;32m---> 12\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[43mget_completion\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprompt\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     13\u001b[0m     \u001b[38;5;28mprint\u001b[39m(i, response, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n",
-      "Cell \u001b[0;32mIn[4], line 3\u001b[0m, in \u001b[0;36mget_completion\u001b[0;34m(prompt, model)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_completion\u001b[39m(prompt, model\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgpt-3.5-turbo\u001b[39m\u001b[38;5;124m\"\u001b[39m): \u001b[38;5;66;03m# Andrew mentioned that the prompt/ completion paradigm is preferable for this class\u001b[39;00m\n\u001b[1;32m      2\u001b[0m     messages \u001b[38;5;241m=\u001b[39m [{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrole\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muser\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent\u001b[39m\u001b[38;5;124m\"\u001b[39m: prompt}]\n\u001b[0;32m----> 3\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[43mopenai\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mChatCompletion\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m        \u001b[49m\u001b[43mmessages\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmessages\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# this is the degree of randomness of the model's output\u001b[39;49;00m\n\u001b[1;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      8\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m response\u001b[38;5;241m.\u001b[39mchoices[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mmessage[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n",
-      "File \u001b[0;32m~/opt/anaconda3/envs/chatGPT/lib/python3.9/site-packages/openai/api_resources/chat_completion.py:25\u001b[0m, in \u001b[0;36mChatCompletion.create\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m     23\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[1;32m     24\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 25\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     26\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m TryAgain \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m     27\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m timeout \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m>\u001b[39m start \u001b[38;5;241m+\u001b[39m timeout:\n",
-      "File \u001b[0;32m~/opt/anaconda3/envs/chatGPT/lib/python3.9/site-packages/openai/api_resources/abstract/engine_api_resource.py:153\u001b[0m, in \u001b[0;36mEngineAPIResource.create\u001b[0;34m(cls, api_key, api_base, api_type, request_id, api_version, organization, **params)\u001b[0m\n\u001b[1;32m    127\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m    128\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mcreate\u001b[39m(\n\u001b[1;32m    129\u001b[0m     \u001b[38;5;28mcls\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    136\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams,\n\u001b[1;32m    137\u001b[0m ):\n\u001b[1;32m    138\u001b[0m     (\n\u001b[1;32m    139\u001b[0m         deployment_id,\n\u001b[1;32m    140\u001b[0m         engine,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    150\u001b[0m         api_key, api_base, api_type, api_version, organization, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams\n\u001b[1;32m    151\u001b[0m     )\n\u001b[0;32m--> 153\u001b[0m     response, _, api_key \u001b[38;5;241m=\u001b[39m \u001b[43mrequestor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    154\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpost\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    155\u001b[0m \u001b[43m        \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    156\u001b[0m \u001b[43m        \u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    157\u001b[0m \u001b[43m        \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    158\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    159\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrequest_id\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    160\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrequest_timeout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrequest_timeout\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    161\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    163\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m stream:\n\u001b[1;32m    164\u001b[0m         \u001b[38;5;66;03m# must be an iterator\u001b[39;00m\n\u001b[1;32m    165\u001b[0m         \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(response, OpenAIResponse)\n",
-      "File \u001b[0;32m~/opt/anaconda3/envs/chatGPT/lib/python3.9/site-packages/openai/api_requestor.py:226\u001b[0m, in \u001b[0;36mAPIRequestor.request\u001b[0;34m(self, method, url, params, headers, files, stream, request_id, request_timeout)\u001b[0m\n\u001b[1;32m    205\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrequest\u001b[39m(\n\u001b[1;32m    206\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    207\u001b[0m     method,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    214\u001b[0m     request_timeout: Optional[Union[\u001b[38;5;28mfloat\u001b[39m, Tuple[\u001b[38;5;28mfloat\u001b[39m, \u001b[38;5;28mfloat\u001b[39m]]] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m    215\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Tuple[Union[OpenAIResponse, Iterator[OpenAIResponse]], \u001b[38;5;28mbool\u001b[39m, \u001b[38;5;28mstr\u001b[39m]:\n\u001b[1;32m    216\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrequest_raw(\n\u001b[1;32m    217\u001b[0m         method\u001b[38;5;241m.\u001b[39mlower(),\n\u001b[1;32m    218\u001b[0m         url,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    224\u001b[0m         request_timeout\u001b[38;5;241m=\u001b[39mrequest_timeout,\n\u001b[1;32m    225\u001b[0m     )\n\u001b[0;32m--> 226\u001b[0m     resp, got_stream \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_interpret_response\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstream\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    227\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m resp, got_stream, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mapi_key\n",
-      "File \u001b[0;32m~/opt/anaconda3/envs/chatGPT/lib/python3.9/site-packages/openai/api_requestor.py:620\u001b[0m, in \u001b[0;36mAPIRequestor._interpret_response\u001b[0;34m(self, result, stream)\u001b[0m\n\u001b[1;32m    612\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[1;32m    613\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_interpret_response_line(\n\u001b[1;32m    614\u001b[0m             line, result\u001b[38;5;241m.\u001b[39mstatus_code, result\u001b[38;5;241m.\u001b[39mheaders, stream\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m    615\u001b[0m         )\n\u001b[1;32m    616\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m line \u001b[38;5;129;01min\u001b[39;00m parse_stream(result\u001b[38;5;241m.\u001b[39miter_lines())\n\u001b[1;32m    617\u001b[0m     ), \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m    618\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    619\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[0;32m--> 620\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_interpret_response_line\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    621\u001b[0m \u001b[43m            \u001b[49m\u001b[43mresult\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcontent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mutf-8\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    622\u001b[0m \u001b[43m            \u001b[49m\u001b[43mresult\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstatus_code\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    623\u001b[0m \u001b[43m            \u001b[49m\u001b[43mresult\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    624\u001b[0m \u001b[43m            \u001b[49m\u001b[43mstream\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    625\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m,\n\u001b[1;32m    626\u001b[0m         \u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m    627\u001b[0m     )\n",
-      "File \u001b[0;32m~/opt/anaconda3/envs/chatGPT/lib/python3.9/site-packages/openai/api_requestor.py:683\u001b[0m, in \u001b[0;36mAPIRequestor._interpret_response_line\u001b[0;34m(self, rbody, rcode, rheaders, stream)\u001b[0m\n\u001b[1;32m    681\u001b[0m stream_error \u001b[38;5;241m=\u001b[39m stream \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124merror\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01min\u001b[39;00m resp\u001b[38;5;241m.\u001b[39mdata\n\u001b[1;32m    682\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m stream_error \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;241m200\u001b[39m \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m rcode \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m300\u001b[39m:\n\u001b[0;32m--> 683\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_error_response(\n\u001b[1;32m    684\u001b[0m         rbody, rcode, resp\u001b[38;5;241m.\u001b[39mdata, rheaders, stream_error\u001b[38;5;241m=\u001b[39mstream_error\n\u001b[1;32m    685\u001b[0m     )\n\u001b[1;32m    686\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m resp\n",
-      "\u001b[0;31mRateLimitError\u001b[0m: Rate limit reached for default-gpt-3.5-turbo in organization org-SoADSeM578ReGFBjktovCGZG on requests per min. Limit: 3 / min. Please try again in 20s. Contact us through our help center at help.openai.com if you continue to have issues. Please add a payment method to your account to increase your rate limit. Visit https://platform.openai.com/account/billing to add a payment method."
-     ]
-    }
-   ],
-   "source": [
-    "for i in range(len(reviews)):\n",
-    "    prompt = f\"\"\"\n",
-    "    Your task is to generate a short summary of a product \\ \n",
-    "    review from an ecommerce site. \n",
-    "\n",
-    "    Summarize the review below, delimited by triple \\\n",
-    "    backticks in at most 20 words. \n",
-    "\n",
-    "    Review: ```{reviews[i]}```\n",
-    "    \"\"\"\n",
-    "\n",
-    "    response = get_completion(prompt)\n",
-    "    print(i, response, \"\\n\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a7aa40f3",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.9.16"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}