06-qa-bot/F1_QA_Assistant.ipynb

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 "cells": [
  {
   "cell_type": "code",
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   "id": "98620c62",
   "metadata": {},
   "outputs": [],
   "source": [
    "# %pip install python-dotenv openai pandas\n",
    "\n",
    "from typing import Dict, List\n",
    "from utilities import num_tokens_from_messages, get_embedding, get_n_nearest_neighbors, memoize_to_sqlite\n",
    "from f1_utilities import wikipedia_splitter, Section\n",
    "from io import StringIO\n",
    "\n",
    "import csv\n",
    "import requests\n",
    "import os\n",
    "import itertools\n",
    "import tiktoken\n",
    "import openai\n",
    "import pandas as pd\n",
    "\n",
    "from dotenv import load_dotenv\n",
    "\n",
    "load_dotenv(\".env\")\n",
    "\n",
    "openai.api_key = os.environ[\"OPENAI_API_KEY\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "63b747c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Optional\n",
    "\n",
    "\n",
    "MAX_CONTEXT_WINDOW = 4097\n",
    "MINIMUM_RESPONSE_SPACE = 1000\n",
    "MAX_PROMPT_SIZE = MAX_CONTEXT_WINDOW - MINIMUM_RESPONSE_SPACE\n",
    "\n",
    "\n",
    "def ask_embedding_store(question: str, embeddings: Dict[Section, List[float]], max_documents: int) -> str:\n",
    "    \"\"\"\n",
    "    Fetch necessary context from our embedding store, striving to fit the top max_documents\n",
    "    into the context window (or fewer if the total token count exceeds the limit)\n",
    "\n",
    "    :param question: The question to ask\n",
    "    :param embeddings: A dictionary of Section objects to their corresponding embeddings\n",
    "    :param max_documents: The maximum number of documents to use as context\n",
    "    :return: GPT's response to the question given context provided in our embedding store\n",
    "    \"\"\"\n",
    "    query_embedding = get_embedding(question)\n",
    "\n",
    "    nearest_neighbors = get_n_nearest_neighbors(query_embedding, embeddings, max_documents)\n",
    "    messages: Optional[List[Dict[str, str]]] = None\n",
    "\n",
    "    base_token_count = num_tokens_from_messages(get_messages([], question), chat_model)\n",
    "    token_counts = [len(enc.encode(document.text.replace(\"\\n\", \" \"))) for document, _ in nearest_neighbors]\n",
    "    cumulative_token_counts = list(itertools.accumulate(token_counts))\n",
    "    indices_within_limit = [True for x in cumulative_token_counts if x <= (MAX_PROMPT_SIZE - base_token_count)]\n",
    "    most_messages_we_can_fit = len(indices_within_limit)\n",
    "\n",
    "    context = [x[0] for x in nearest_neighbors[: most_messages_we_can_fit + 1]]\n",
    "\n",
    "    debug_str = \"\\n\".join([f\"{x[0].location}: {x[1]}\" for x in nearest_neighbors[: most_messages_we_can_fit + 1]])\n",
    "#     print(f\"Using {most_messages_we_can_fit} documents as context:\\n\" + debug_str)\n",
    "    messages = get_messages(context, question)\n",
    "\n",
    "#     print(f\"Prompt: {messages[-1]['content']}\")\n",
    "    result = openai.ChatCompletion.create(model=chat_model, messages=messages)\n",
    "    return result.choices[0].message[\"content\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "252d3928",
   "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>Link</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022_Formula_One_World_Championship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022_Abu_Dhabi_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022_Sao_Paulo_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022_Mexico_City_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022_United_States_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2022_Japanese_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2022_Singapore_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2022_Italian_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022_Dutch_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2022_Belgian_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2022_Hungarian_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2022_French_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2022_Austrian_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2022_British_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2022_Canadian_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2022_Azerbaijan_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2022_Monaco_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2022_Spanish_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2022_Miami_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2022_Emilia_Romagna_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2022_Australian_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2022_Saudi_Arabian_Grand_Prix</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2022_Bahrain_Grand_Prix</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   Link\n",
       "0   2022_Formula_One_World_Championship\n",
       "1             2022_Abu_Dhabi_Grand_Prix\n",
       "2             2022_Sao_Paulo_Grand_Prix\n",
       "3           2022_Mexico_City_Grand_Prix\n",
       "4         2022_United_States_Grand_Prix\n",
       "5              2022_Japanese_Grand_Prix\n",
       "6             2022_Singapore_Grand_Prix\n",
       "7               2022_Italian_Grand_Prix\n",
       "8                 2022_Dutch_Grand_Prix\n",
       "9               2022_Belgian_Grand_Prix\n",
       "10            2022_Hungarian_Grand_Prix\n",
       "11               2022_French_Grand_Prix\n",
       "12             2022_Austrian_Grand_Prix\n",
       "13              2022_British_Grand_Prix\n",
       "14             2022_Canadian_Grand_Prix\n",
       "15           2022_Azerbaijan_Grand_Prix\n",
       "16               2022_Monaco_Grand_Prix\n",
       "17              2022_Spanish_Grand_Prix\n",
       "18                2022_Miami_Grand_Prix\n",
       "19       2022_Emilia_Romagna_Grand_Prix\n",
       "20           2022_Australian_Grand_Prix\n",
       "21        2022_Saudi_Arabian_Grand_Prix\n",
       "22              2022_Bahrain_Grand_Prix"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('f1_2022.csv')\n",
    "df"
   ]
  },
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   "source": [
    "@memoize_to_sqlite(\"cache.db\")\n",
    "def wikipedia_api_fetch(article_title: str, field: str) -> str:\n",
    "    base_url = \"https://en.wikipedia.org/w/api.php\"\n",
    "\n",
    "    params = {\n",
    "        'action': 'query',\n",
    "        'format': 'json',\n",
    "        'prop': 'extracts',\n",
    "        'titles': article_title,\n",
    "        'explaintext': 1\n",
    "    }\n",
    "\n",
    "    response = requests.get(base_url, params=params)\n",
    "    data = response.json()\n",
    "\n",
    "    if 'query' in data and 'pages' in data['query']:\n",
    "        page = list(data['query']['pages'].values())[0]\n",
    "        if field in page:\n",
    "            return page[field]\n",
    "        else:\n",
    "            raise ValueError(f\"Could not find {field} for page {page}\")\n",
    "    else:\n",
    "        raise ValueError(f\"Could not find page {article_title}\")\n",
    "\n",
    "\n",
    "# Loop through the DataFrame and fetch the content of each Grand Prix\n",
    "df['Page_Content'] = df['Link'].apply(lambda x: wikipedia_api_fetch(x, 'extract'))\n",
    "df['Display Title'] = df['Link'].apply(lambda x: wikipedia_api_fetch(x, 'title'))\n",
    "sections: List[Section] = []\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
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   "id": "b6a0b826",
   "metadata": {},
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    {
     "name": "stdout",
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     "text": [
      "Section is too long: 2022 Formula One World Championship - Regulation changes, splitting\n",
      "Section is too long: 2022 Formula One World Championship - Regulation changes - Technical regulations, splitting\n",
      "Section is too long: 2022 Formula One World Championship - Season summary, splitting\n",
      "Section is too long: 2022 Formula One World Championship - Season summary - Opening rounds, splitting\n",
      "Section is too long: 2022 Formula One World Championship - Season summary - Mid-season rounds, splitting\n",
      "Section is too long: 2022 Formula One World Championship - Season summary - Closing rounds, splitting\n",
      "Section is too long: 2022 Japanese Grand Prix - Race, splitting\n",
      "Section is too long: 2022 Belgian Grand Prix - Background, splitting\n",
      "Section is too long: 2022 British Grand Prix - Race, splitting\n",
      "Section is too long: 2022 British Grand Prix - Race - Race report, splitting\n",
      "Section is too long: 2022 Monaco Grand Prix - Race, splitting\n",
      "Section is too long: 2022 Monaco Grand Prix - Race - Race report, splitting\n",
      "Section is too long: 2022 Emilia Romagna Grand Prix - Race, splitting\n",
      "Section is too long: 2022 Emilia Romagna Grand Prix - Race - Race report, splitting\n",
      "Section is too long: 2022 Australian Grand Prix - Background, splitting\n"
     ]
    }
   ],
   "source": [
    "# The precedence of points to split on if a section cant be fit in max length\n",
    "split_point_regexes = [r'\\n==\\s', r'\\n===\\s', r'\\n====\\s', r'\\n\\n', r'\\n']\n",
    "\n",
    "\n",
    "# Calculate wikipedia content for each row in the data frame\n",
    "for index, row in df.iterrows():\n",
    "    page_content = row['Page_Content']\n",
    "    for section in wikipedia_splitter(row['Page_Content'], row['Display Title'], token_limit=MAX_CONTEXT_WINDOW, split_point_regexes=split_point_regexes):\n",
    "        sections.append(section)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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   "metadata": {
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2022 Formula One World Championship - 2022 Formula One World Championship:\n",
      "The 2022 FIA Formula One World Championship was a motor racing championship for Formula One cars, which was the 73rd running of the Formula One World Championship. It is recognised by the Fédération Internationale de l'Automobile (FIA), the governing body of international motorsport, as the highest class of competition for open-wheel racing cars. The championship was contested over twenty-two Grands Prix, which were held around the world, and ended earlier than in recent years to avoid overlapping with the FIFA World Cup.Drivers and teams competed for the titles of World Drivers' Champion and World Constructors' Champion, respectively. The 2022 championship saw the introduction of significant changes to the sport's technical regulations. These changes had been intended to be introduced in 2021, but were delayed until 2022 in response to the COVID-19 pandemic. Max Verstappen, who was the reigning Drivers' Champion, claimed his second title at the Japanese Grand Prix, while his team, Red Bull Racing, achieved their fifth World Constructor Championship, and first since 2013, at the following United States Grand Prix. Mercedes were the reigning Constructors' Champion.This was the final season for four-time World Champion Sebastian Vettel. Seven-time World Champion Lewis Hamilton endured a difficult season with Mercedes, failing to secure either a pole position or Grand Prix win during the season, the first time either occurrence had happened in his Formula One career since it began in 2007.\n",
      "\n",
      "\n",
      "Estimated Cost $0.02\n"
     ]
    }
   ],
   "source": [
    "chat_model = \"gpt-3.5-turbo\"\n",
    "embedding_enc = tiktoken.encoding_for_model(\"text-embedding-ada-002\")\n",
    "enc = tiktoken.encoding_for_model(chat_model)\n",
    "\n",
    "# Calculate the total number of tokens in the Page Content Column\n",
    "print(str(sections[0]))\n",
    "\n",
    "total_tokens = sum([len(embedding_enc.encode(str(section))) for section in sections])\n",
    "\n",
    "# $0.0004 per 1000 tokens\n",
    "cost = total_tokens * (0.0004 / 1000)\n",
    "print(f\"Estimated Cost ${cost:.2f}\")"
   ]
  },
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      "Cached result found for 6ee038f7f4ac7b92578c25607be931223f703920f4cbbdd89d8161157c47a4af. Returning it.\n",
      "Cached result found for cf131c891a045fb6531696d0aa78fdf1f6d5c0707c1a00437c99db397c7c38be. Returning it.\n",
      "Cached result found for fc73fe8165ff2c95416b89a21a257f57df01a48f4a06d1f1749bf9ecad0c4a8a. Returning it.\n",
      "Cached result found for 8308be37c3d9f85e6ed097404a2e0212e457cb48c1e9587a8d13b251b1dc24f3. Returning it.\n",
      "Cached result found for ca0d0f69e6a04ba22253713bdc0b74aef17ae8a1db108b2db4a43d8e78cc3006. Returning it.\n",
      "Cached result found for c70685ff7c00c7985cfc05e8f7afbf976d4ef8c43daf3b931c629a5f876295d3. Returning it.\n",
      "Cached result found for 37bb2e767965f2ed2303abe54c39e5991eeaf19d55f39b77a08d55a4c31d6585. Returning it.\n",
      "Cached result found for 96f771be965d2e5efb3379ec17077e8d2aa2f3c642a023793983bf9271fe0ef7. Returning it.\n",
      "Cached result found for 106ae7bbecf77226acd774590beeb81174d9b6cae458d3b7d2272b405ec51982. Returning it.\n",
      "Cached result found for ce9ad853b6f057c07a39ce8a9848dc515cfc8a6876ee4a76ace808d2cb503804. Returning it.\n",
      "Cached result found for 9877bcdd86cac8de73dc8ef5a9e88bcf43059f0b23e9c4dda70d1a39eb9bae16. Returning it.\n",
      "Cached result found for 3d0b32e06574125613f68cd4a38c9ab4dacf3ecab5b8c978daff592f532b49b3. Returning it.\n",
      "Cached result found for c4aae3cca797d61dd28faadcb31ed7b33f795d9be19351d08991d45e24f37807. Returning it.\n",
      "Cached result found for 6ea353196ad2651d00a9e3bd31da4826e97290c813f41dc8dbe28ec2c9917834. Returning it.\n",
      "Cached result found for 23c002e5e14a3333407ad380a57a7a93088cc82d84919af3847b7420abf61e12. Returning it.\n",
      "Cached result found for 7821a528d94132f2831ac78e9d55802cd888fea75ed2402088d34408307824b1. Returning it.\n",
      "Cached result found for f98757b07d7b36604e709b58875b1ec2607252c7899d6bdcdd9f346c95215c19. Returning it.\n",
      "Cached result found for dbe5a115f5995f098dc498e774949632d0b6cc95ad28666e6b270e80583830b6. Returning it.\n",
      "Cached result found for 6d0b9ece7d56a694272a3b3cf4775d5b948b5eca55dded0f1c7de14d5733ca46. Returning it.\n",
      "Cached result found for fa75b701ed35f75ae66b7d0b1a88d182f9c8dc2b14e832a98d0d84d4033c0755. Returning it.\n",
      "Cached result found for b8b334d050027f99cb6bc7a1f69e500bf1003c558a221bd28e5ff283f0c1e6ca. Returning it.\n",
      "Cached result found for 4230f69b6e4ca36ad6e5bbf04bcc855f4f93036edd6d564dfa2281f28b16347d. Returning it.\n",
      "Cached result found for 6e3b7b50973ec2eb53fc812e15805dedbc15810aac83ec2f9534cfb5ba780b08. Returning it.\n",
      "Cached result found for 32a872952234b5f047fe57300772aed53aa09710dd571a3d6214aa3e45e937c4. Returning it.\n",
      "Cached result found for 49c44f966599ebb475785d6180384abdfdcefc94fbb89e5815d16cfd2e85b791. Returning it.\n",
      "Cached result found for ba895d8ac4c2db0813b2701015f7c63bbde96b0d3d1e36ca64f0d562bbf46520. Returning it.\n",
      "Cached result found for 3f990b2f8284b74f96e7e22821c67b29723187dd22224cc6ea2314fb0a1287f0. Returning it.\n",
      "Cached result found for 28498831f17eff7e53e39c4c666a6547a75e9807946dc777815493c8b14691b2. Returning it.\n",
      "Cached result found for cb882c4eb35faba76207dcc13437bfff8ff06d6a6e128b797950efc55b5ddaef. Returning it.\n",
      "Cached result found for 5a14597717ad7d8ddcbfa4cdf13af360b2daf748b6d9700efec10b7ab61ad87a. Returning it.\n",
      "Cached result found for 652a859ac0ec7cea3089163e1c604500ff2314b612c0e1754d4ed97f7ae4f972. Returning it.\n",
      "Cached result found for ec59813a14515e3415b9d518dee11c23e315ede5995a6af9ba122fc824d8ab76. Returning it.\n",
      "Cached result found for 201bed7dd2219d2dd3164c55f2192c3d674ff0b8b41402a89a996c0d0a5ca060. Returning it.\n",
      "Cached result found for eaf4565f14f3fe440ac1e5f5802f785dacc5b7f240101c910653ac0817d6f34e. Returning it.\n",
      "Cached result found for 087b13eeddb6af486ffa5533315df1423f32eaac5e9a3f571119d84490fc835d. Returning it.\n",
      "Cached result found for 0c5c60f2953f8951e92719dbbadd243a2dfcbbc3bd4819a6b2871606b6ebc544. Returning it.\n",
      "Cached result found for 8669c2183d2921687237c430efdb05f62d7dbbe8f60ab8f5a53f4e71e8561229. Returning it.\n",
      "Cached result found for 7e0fbd3ed24bc1c94ff5c5d4fcfb59ffc8d8f87b38428c84a0dbd737d1bdb138. Returning it.\n",
      "Cached result found for 9d8bc037171df043b4f25e585e72b9c404ed1028efe6144df435b231d0368fd8. Returning it.\n",
      "Cached result found for 170c371246dc24a7f618523bb1f2ca82b8a6e381695cdbd1868a446380403ef3. Returning it.\n",
      "Cached result found for 5876ab12ccfcbfc8d3cebdf0f2658c461b5656a115aa41ee7ccb1701d8a989bf. Returning it.\n",
      "Cached result found for 991447bf44abca71008c15f84507226c2f0b6865aef2202850cb5788f86c4c45. Returning it.\n",
      "Cached result found for ad5e4ea7d081a4de3cfaa5d4851cdc419951b913ed1000806ef5d7005c5faaab. Returning it.\n",
      "Cached result found for 4f0abfd6df3c2fd8eb22d9bd9b2103742128afda07456d213e9d7f707ab67aca. Returning it.\n",
      "Cached result found for 1f628d6ec3141189b3641b3066605d0f4b9e845c22399ab0d2150e8095478020. Returning it.\n",
      "Cached result found for 0abece8d72b9846751854447f40ece05f9f92f5fc57d6ffe3d6afb16b97e3f8b. Returning it.\n",
      "Cached result found for aca22dc9f93b5fb9fb4cc5b2e494c2609cbe115649c37d0fe9c131aa0cd88b2b. Returning it.\n",
      "Cached result found for c711688785a8db70ad268245375f2888e0e5c647f54676254958d1a7ebc7f959. Returning it.\n",
      "Cached result found for 782fe21b073d7aafc8505f0186b72bb9d87bec7c9cec64b42190e96f2c258c80. Returning it.\n",
      "Cached result found for 6276b15dc08771ece399162f78fbacf5e357950a26f28c9ced140292256f468c. Returning it.\n",
      "Cached result found for 971f7d2b4727e0fc9be9017a7879750629a09860925ead126c96ce05844b4f8f. Returning it.\n",
      "Cached result found for d077616e8eab538fbe28a9c8a3dfcf3d59f37fd5ef84f973b40063a3c6a6cf99. Returning it.\n",
      "Cached result found for 29f41c25c2fda0c9f8772fea49b8a0422f2a4b21764ea0c7acc1e7f310e90a80. Returning it.\n",
      "Cached result found for 78a515cbc5199198c45aa147f1ceb960912ce5dabaf8decfec92c19a03befa74. Returning it.\n",
      "Cached result found for 7d637313055dcaec4130cc3c42e1932d7cedf7fa1ad7a90d55fae704dfc40644. Returning it.\n",
      "Cached result found for a20dee2ca8d8b559516e24021cf66b4a179d3b4fefa26caf32750d4821f99db1. Returning it.\n",
      "Cached result found for 449c0f1aeae624a427f6e2f41b815e3916b6eeb8f1a4213c439d8fa4ff1a609c. Returning it.\n",
      "Cached result found for 0d667086b87514e977ee10416793c256bd26ede0d64d7d58d1101e00927d3d62. Returning it.\n",
      "Cached result found for 3f12e15b08264a1138f257c431c33428649e24a2da0658224bdefd0721863814. Returning it.\n",
      "Cached result found for 707b759775fb45c4da33f326c68206cb285c2540fc972f96d521a848a90374bc. Returning it.\n",
      "Cached result found for 7f829455a9526f7e3062bb757364f376e76adf86f2db7ff885d955a182303878. Returning it.\n",
      "Cached result found for 4969b8f928980241d49bb9625fa8fae584a4a4baf02ac38bb4a437a3cc9a4bbf. Returning it.\n",
      "Cached result found for 7eff573d88fb2f6cdeff8c23f3efa86eabea09eca21072963abf9b57a5c517de. Returning it.\n",
      "Cached result found for 8f4d8cbbeaca17ee1ae33add679ba9b334ab28feb43a202a0ab6a24596ca0205. Returning it.\n",
      "Cached result found for 69923c518573c682d85043cbf031c8768327f7e4d9167cf5c91fe2d31f4f77c2. Returning it.\n",
      "Cached result found for 88c36fc95de02b6a574d47ae25b1c3a188bb1b4856205bef11b61af1ba640c38. Returning it.\n",
      "Cached result found for d4e020eeebcd8cec695b4a45dbd1bbaff62d0ea42c9a4e3586a9d9feb088d26a. Returning it.\n",
      "Cached result found for 11fef0b26b868f3af54a677c58a7907353ae9f1363ecc890e6d8664148ff9a0e. Returning it.\n",
      "Cached result found for 5d1a1720628148dd1693bfe4b0744c1787cc3410c79f3cabfe329e9b978cbfed. Returning it.\n",
      "Cached result found for eb35c8963b9aeac75513b6ed22aedb63070f05ff0c938e155f30a9212dcb494b. Returning it.\n",
      "Cached result found for 1bd94a2d07b58eef3a8dc830ac3a06edbbd595a17b93f5e63b5431881bcf6666. Returning it.\n",
      "Cached result found for 3e2afffd4fd8d383fe3950afda0f13d9b6d2295d42766074833c6a2b5d43e13a. Returning it.\n",
      "Cached result found for 84ab5d4d105a984e24f80529e21f49cf761e7e1599ea16899a45fbf275ab23e4. Returning it.\n",
      "Cached result found for 75173b1b9e8c807ed86c825d0ab76a4574c1b8e7047ededaee330886be770d6b. Returning it.\n",
      "Cached result found for 651a23bab98c3317307ae228f3eca1142ebae6100632c58ad417c7c3dcc86d12. Returning it.\n",
      "Cached result found for 4574d154a94f05f9932a2c9a19e2d87243747597444ad1d0f83ca28785ab99b2. Returning it.\n",
      "Cached result found for 72a2128785d17658f9e1b8f25a5b33ffbd9a32b5cad05059d0e6b147fba4c7c4. Returning it.\n",
      "Cached result found for c4340e37b1377a38d4ceed9f10e11e5f95810ef287ff864439007d41cd3d542d. Returning it.\n",
      "Cached result found for 309de2b5f37a0ad67dd42c20124fcf6fa3b4cf960d87da1af941ee1929c08986. Returning it.\n",
      "Cached result found for 72b44e8c3144e1b289903b0d2d9475fa9cd0049b8ed996c66ffeaec4d48f8c2f. Returning it.\n",
      "Cached result found for 68e324078bb21b02670f606da61f1be9fe8176db93da81bc3d317d4756bd3729. Returning it.\n",
      "Cached result found for a38cbbf360bf7f259380cc31104c31dd8addaed224a00e18e24b7ac41b6868cb. Returning it.\n",
      "Cached result found for 6a6e8819a1ae878863e7f53f81cae39b85c521ab6677de34e705741c755dbd7a. Returning it.\n",
      "Cached result found for 90a7500956e8ce0abcab848eaaf4e4c2ad30a6408bbe87e170b4606c77324eb0. Returning it.\n",
      "Cached result found for 41eb565aa437d41422ee57f75f49006bca35be44ad7f667c5e84145351f324fb. Returning it.\n",
      "Cached result found for eaa685ee0dc948ee7b0ec354a0c35f861de58a5d220cfc61c2cc5c6257426cc4. Returning it.\n",
      "Cached result found for a1867750beee0c200381456d74920668cc8eb5097bc93ca30411a47d4da311af. Returning it.\n",
      "Cached result found for 59ad217ec20a66b3576553e5d61dd2dec90455c15f7dac6faca9b1645d51094b. Returning it.\n",
      "Cached result found for 81d0a29982665793fbca332f34f99a2968ea4ddaa866c86b31f4e4580998eaf9. Returning it.\n",
      "Cached result found for fcc2bc3fcf1aeb5d05c46232ea464f8ed63dd0bcad350b9e56d78be2ec24933b. Returning it.\n",
      "Cached result found for e2b41e2c6043eb924307848da542f6e9f2656617f5e5d5fcca03759e0fce7521. Returning it.\n",
      "Cached result found for 32fb7df66486581238cd5e797ca65f514989386775d5f522bc1df0088a156319. Returning it.\n",
      "Cached result found for de2ed81540489a67e6448025127551d3c78ef6a76c29d1c3d1597b2aca9683eb. Returning it.\n",
      "Cached result found for 5ddb67cc24dc4ff925c0f0ab21a86a9835e39fdf290de78b751261ee60d24867. Returning it.\n",
      "Cached result found for eb2acb8cfe69b45a39586c528e65bb5c83117029c3069d5c7ae1dfe3eac7a0f2. Returning it.\n",
      "Cached result found for 35554d99c4bd7e387bdac59e2643b98faa90214edec84433340413d90b578761. Returning it.\n",
      "Cached result found for be2b38314990104324e3a0357f4e34f32d7c0c9bf77a92bbcbefecdb4d0bcd0a. Returning it.\n",
      "Cached result found for 5021c7ffe26a4588d45e57b4730e904d1a0569903abd786b28de1f75ac30285e. Returning it.\n",
      "Cached result found for adb53caba779c092c56e31eceb8ee4831a2d117bbb4e5721f49519c0f938adf0. Returning it.\n",
      "Cached result found for 545499579105e846d9d98ee9788dd338feb98055606b69df9eee7cf93e3c5666. Returning it.\n",
      "Cached result found for 4b664820ecce6f4c8c15ca9f211affc3890d3d72490c4a5e1ea6434e614d9667. Returning it.\n",
      "Cached result found for 20bac3d37c16fa7d031f2313976ff7068f3781ca272970b6998e98d55b0c5425. Returning it.\n",
      "Cached result found for fdd8e7c8d62469696831d2b7bb8ebad3e784b1207df05db5754ecb5d258961b4. Returning it.\n",
      "Cached result found for fcb7108df6c4f28b4be7461b5d9ca1ae85886b78864eef88b5233179237d4677. Returning it.\n",
      "Cached result found for 4b3a76142df00276064b8d108fe65e18a308bfcc5e4036ec1200ecbb953fa4a6. Returning it.\n",
      "Cached result found for 02bf2efde73fba272dcaa3f7cc97bb6a1bf9e9025f85f5249d78a662b25f3ac2. Returning it.\n",
      "Cached result found for 318ce98987cd4310a7ad0c3de2c9205d90809d899a35f32451d03913068fa32f. Returning it.\n",
      "Cached result found for e7f195c8eb1de8a6557dea21bec8f1a5a69ad5c148b4e01b8819ffb7f64a7bc1. Returning it.\n",
      "Cached result found for f5b0845d5bbf1f839033216cf324620fe7e5dae25480cd0367fa19d1b0973e47. Returning it.\n",
      "Cached result found for 8f89ed34aa012a9160064b42f1a22a74ea6bc4e82a392922aaf84b03ce947577. Returning it.\n",
      "Cached result found for 5af34c13a568e2a2c61f7031d2395f36bdaabeb4068a731c58f6046f0027cc50. Returning it.\n",
      "Cached result found for faadefa024304c63365a79b489135794660a18c23c9c42af129842def4698f63. Returning it.\n",
      "Cached result found for 619b226b94db7a4417093ad36b6f5775ac0db325fa2287a1cc14659623ac92c3. Returning it.\n",
      "Cached result found for b1532066bdab7d9c6d85aa6289d57d6dfa4aa9bc47df5a335cf0dead5c1979a2. Returning it.\n",
      "Cached result found for 21878758a7642ae9c18cc6741f0cb705fe24283482383f485dd3627143ba5d09. Returning it.\n",
      "Cached result found for bece9b6e7d716208ab1476b94fdc7d9e4997186226ac1584b29d520909c930db. Returning it.\n",
      "Cached result found for 48f23e63196668308898183428850dfdc3760d04b98d05f266e1820f463d979f. Returning it.\n",
      "Cached result found for 16b7e63efc59c05a050bbc5ed88765c285f61c5b7c0dccb52bc15d6751f3208b. Returning it.\n",
      "Cached result found for 32064ce1cb3f53c3b8b14bb0b0f664b374b1da75aa1969dd9b8fd35fda38f7a9. Returning it.\n",
      "Cached result found for 1078c27ebcd3f2d419e77b802e78456b062bab2ca10ebf8a48647a2c2bd05adf. Returning it.\n",
      "Cached result found for f28081072fd5cc11a95c3e800e211ced6990ba05a9e0189f6ede13c038e9ec4e. Returning it.\n",
      "Cached result found for 633597506ba9fe78ff9616c5cfed311c6c12d1915480744855bf4614efd5c0b7. Returning it.\n",
      "Cached result found for 71ff79dfd1f02285693bed995c3dae3065c990e45de23b207861d3f18dd5f622. Returning it.\n",
      "Cached result found for 9db91af9cdacc08a49e64663463214be36a016e19d58e732959e77da4e3a72a4. Returning it.\n",
      "Cached result found for 7d36e5787422b33c3a16b49cb2f33cbdce17265c32dca7716b6b8091487d07ee. Returning it.\n",
      "Cached result found for 0290f8e4e030054256fdbee63cb7ad9ffa4a01a2643fabc751b868a06adf46eb. Returning it.\n",
      "Cached result found for ff44d68e0863254bbe5b2ec579ff9b0b9d633f60eaaa05cfe00de7e31f7fd144. Returning it.\n",
      "Cached result found for b4059d3824597589a5208c679948d9977eec8dd5bb540d943d0f9c2f226ec7d4. Returning it.\n",
      "Cached result found for 55426c18f41f96ca9f773bef00cc3052aaea594182bd6ee85c9544e2c5e74051. Returning it.\n",
      "Cached result found for b28c4b10e9ad66a3b442dc83eb9dcb66fb30d96f4bfe26beed2ab177aaab3fef. Returning it.\n",
      "Cached result found for 6d7023900aad94ab5d72b4abfa3089b1e91da3a475e47835dca69633214d3175. Returning it.\n",
      "Cached result found for 1091338c7474ba505d72d9148f90e6e700b82dd37567cbf594bace41f919fca5. Returning it.\n",
      "Cached result found for a7f7dd3795c04e246ea4bee078ec81bf140b86bf75628a43df68135115c01d01. Returning it.\n",
      "Cached result found for d940e6152940600c73e59ce5f044d6a25e7e00e1e47f45191f898c35a5a6b981. Returning it.\n",
      "Cached result found for abf208c37b6ea7289a3b020b6f76d83a22d36b19f3b70ab5624e36fd191909f5. Returning it.\n",
      "Cached result found for a1c539c127373c236757e967cfb9ad71b07b86a5e53fec9abbe6dc85b416304f. Returning it.\n",
      "Cached result found for a5455756037ae6f88ed611d94186471ac312b3c85917e273047ddd5410831531. Returning it.\n",
      "Cached result found for baacb732c03d6534a65e0636b2c4d0a1e386a24ff6cb8d17704a5fe8f8bb6ca3. Returning it.\n",
      "Cached result found for 4488382fc0bbcae7a6efe10b925dc4145898ce9f03325cb9836d050f48001066. Returning it.\n",
      "Cached result found for 37aa783239c596e64af55847962469ec162905dddb985d4b54188131d15e9ac3. Returning it.\n",
      "Cached result found for 3fe01488ef22e34c6bfc1ed4073eabe7744435cbb107751d8d6526a409173938. Returning it.\n",
      "Cached result found for 0c7a847baaea244692adb1f191c1f8a4310ccce53cb0fc2f19ef8d7dc28226b1. Returning it.\n",
      "Cached result found for 59370edf6a6846be254f07d00bf969a2bdeca4cc33dacc66a2ae2bc02544c898. Returning it.\n",
      "Cached result found for 59487ee96b72c5384aadf1c1bc0c40b9853f8bb971d28175d742bc4a9b9b3d43. Returning it.\n",
      "Cached result found for b105bc51c42fd67058a1325bc108402a2ad33dd8f70770d37fdaef99f574d138. Returning it.\n",
      "Cached result found for 5244119ef6ecbacdba58ac591b679e1378739dfa5a4aa8b49a8179098c968667. Returning it.\n",
      "Cached result found for 9e0f05c24f7f30c0618452dccd9f12e4407409d733ccbab6a8ba3621719e07e0. Returning it.\n",
      "Cached result found for e4bd0c51ded74625db9b91053b52e7063c1d9f8b1c212e3290602679f917658e. Returning it.\n",
      "Cached result found for ddc302a4be4b65e1acfb050fdf726a9eb2333354833f0b59c8ac1e59d48551ff. Returning it.\n",
      "Cached result found for 2b68b99eb2bea45164a4be6f462795262b7b6a6d567f0e3f9c240dc97186cc10. Returning it.\n",
      "Cached result found for 44bd80e02067862876bcaf7d8fc580961904562d2dc94562df6c95258b13d18f. Returning it.\n",
      "Cached result found for 054d396fc24424423478aebdc95f074d400f1bd52ff43589be88410ffe9f2ab2. Returning it.\n",
      "Cached result found for a4400a65cc57c73e25e22f41e32d9a7a11b6b00569cec36f73148b38583e6436. Returning it.\n",
      "Cached result found for 030df13403ae30a2eb93d5da2fd48ea4b601292b4d4112963196c53617ad27d7. Returning it.\n",
      "Cached result found for 53772bef3d42532a1c5217cb1e3251620c88cc19664402c2a1509d37831a11c4. Returning it.\n",
      "Cached result found for 0c6d03c0507fa01ea3e41f817bbddcaef6cae4df1b98593fbd12c733e125e596. Returning it.\n",
      "Cached result found for 933abcbf804a48b4ad21144d59b5a86bce688809fbc9105e72bb75cc5af4fa86. Returning it.\n",
      "Cached result found for 8e12a98dcc03048b9aa9f58f836a0bec2bc01fead7f9c121f5c335fd69fc63b3. Returning it.\n",
      "Cached result found for 12558fba9134a8968a26c65fbdc0416533de72c45b47ea8e28b8fc0a299bddcd. Returning it.\n",
      "Cached result found for 9e8614918532a56d1d73586190addc318c1217a49ddb89fbb129987bd7a75ae2. Returning it.\n",
      "Cached result found for 8e09d27b700b9b52a900945b4fda29cef485148fff1963c48ac08e8446b830df. Returning it.\n",
      "Cached result found for 21acdc7122464ea049318e7bcf5b7eabb2eb94bb4b783e515063b86243fceb73. Returning it.\n",
      "Cached result found for 9c99c9dbbba18b41779f3848862fce2c2f44cc11034e6df3587cec21b16c3af2. Returning it.\n",
      "Cached result found for 4807808dfaa2484dd527d5791ac84d4f2940a01720d43fddbbcac710ce384eaa. Returning it.\n",
      "Cached result found for e9a677e5a9612f61442a0ccbceed4467cf0a20e6d1c0e15264bb689a2ef8c85a. Returning it.\n",
      "Cached result found for ed12445cddcdc33ecafbbe1395d5e9bb730b7817a036d93c25c9df9ca901d6ac. Returning it.\n",
      "Cached result found for 5ba72fa9d052ae3a41cd5b7ae0a4a45d5ab45af6e388bb37af792cec2ef8f779. Returning it.\n",
      "Cached result found for e09fa7325a890e7a736dd65f2cce3d59926a3c1a93576f7e31a990ac46be8c55. Returning it.\n",
      "Cached result found for cc38cd30ce717b33d1474cd0cec967cca6b34b473fdccaa16a9d269c724fc1c3. Returning it.\n",
      "Cached result found for 3c31cb399dd4fbb544946dc54de5788862ce339b3dfa09320006793a06ea21eb. Returning it.\n",
      "Cached result found for 55101f023b43cbd4d4a066456899bf243112f769bacb112b3a74277d906426a2. Returning it.\n",
      "Cached result found for fb7981d0bd4c77301f5d354141a2a5562030bff2dde302022b9239f4a6234596. Returning it.\n",
      "Cached result found for 8ee8202766f71a82ba05f372c700b4f2c4dc3f2a37bf4ee0d5c43ad3bb49038d. Returning it.\n",
      "Cached result found for 91f75e0b97cdd926fc4563a1c449edc6bee4053739ae04d74863e60d4a318018. Returning it.\n",
      "Cached result found for b17fa35939025e8992bff5c31a59b671bad8e4e3459e1668447153cdd9870491. Returning it.\n",
      "Cached result found for 8ecf913bcf76528b792c1000b03335c8d9a71e6a2f4d7f2d333e4c03445eebca. Returning it.\n",
      "Cached result found for de1e8669b1abff8de0afda8a204d1821d615042a0187463c0cceb5d1ad19a37c. Returning it.\n",
      "Cached result found for facba60be47aa77c02a0dbe0343605a399b0a5414ea5380a99a4b61d67c300a5. Returning it.\n",
      "Cached result found for d7b1f2241e263fbd51db809b7bb5382c1356f924919fd1bfb8d4e7bbea1c228f. Returning it.\n",
      "Cached result found for ac82d950c3b8c20168a4ce6b2e76f78caa008f3af532dd1c0c8022283f18730d. Returning it.\n",
      "Cached result found for 07b31b55ee0232b7282a8d373d20d586b818483105d4e7283007246dbddec68d. Returning it.\n",
      "Cached result found for cc19a7f82b090bd4716057d63db112fe7672bab255273ccf178c749268f0cff9. Returning it.\n",
      "Cached result found for de6ee89c08a69b032595aeb3ce022042e4466a4f93ad59d891f3817ac91707ea. Returning it.\n",
      "Cached result found for 4c29ed081c5d290fe977b5b1047c268629f952ec2a925a759fd52664c45e11f6. Returning it.\n",
      "Cached result found for a32b6f09fe30262a8b51397e373e49e267b68abc3e090fb1404f46f925c95106. Returning it.\n",
      "Cached result found for 4b5faa2b9c4f313cdd2137df2f293395578c473f502b351c922bd80c3e66f809. Returning it.\n",
      "Cached result found for e7edb12ab28166a5b27868521b678feaee4469842605701db49143a969bfa1d7. Returning it.\n",
      "Cached result found for 874492ec65e7b41fb2b534de9f8390c378b0bce817185d45c32b8b31d1e66b50. Returning it.\n",
      "Cached result found for 85801cb52bafe544c3a9c8f543a24c512f049c8b6bfdefc7e74a837d06e910ed. Returning it.\n",
      "Cached result found for cc57e4b252f468c3531d60184a644421dfd7618ac5889d3e5e6768747e57a8ca. Returning it.\n",
      "Cached result found for 5f9dc3348f7faeff39a4842f7991d8e5729726f9c4d0d4a34576ff5b638e52e6. Returning it.\n",
      "Cached result found for 6b7f53577e743fd00d530ee3773ab3d612474d60e7988bbe30db0bbc8cb80ae3. Returning it.\n",
      "Cached result found for 61bfb2b73ca13e06fe556fcd854e2c7277b9f313830647ce73324ae1a5a29332. Returning it.\n",
      "Cached result found for 209b57ae1c23c8cd2f7fa385a8ce282c346b2e0454bb50293da0f77c40671a52. Returning it.\n",
      "Cached result found for ab904785e562ce0546f50bf0293d12a8b10787d96f48c2b7fbc34aa4f10504fe. Returning it.\n",
      "Cached result found for f483a5d3e183631ab033c05de41c6fb54ac80cc8262faa1eb23b0b217a7f5a27. Returning it.\n",
      "Cached result found for 0e3ef10389e7a0e0225f0377a7efc186b8dc6a03a1b60aab6527ed09a645feb4. Returning it.\n",
      "Cached result found for 8a82d2b9f311adb659382a270177d0abcfeb904d3e3b5a0c62bd1f6bf89fb706. Returning it.\n",
      "Cached result found for 85b9e08b3a10ba1dc49264ad084b5c60b0fce0c4e269f266a44e7731bfceca3e. Returning it.\n",
      "Cached result found for 238f9461dafb94ef7b36295c7952a407ba2f23e96d0b68c0bd5816ff57373bbb. Returning it.\n",
      "Cached result found for f821241791b82d9bed7b287d5f12365882f50f116d15baf1b07e72271a96188e. Returning it.\n",
      "Cached result found for 8fd941308e58bd3c414cd9c3ce6b2a0361aa094d761ec03f9cf7909652aaf06a. Returning it.\n",
      "Cached result found for 4e354f095eb4c1c926fb15bef2a5c2e876c5a4066e13f3f111b3030bef30a0b6. Returning it.\n",
      "Cached result found for 93d3b0f8299046407e062dc5ec9f504b0a21433901a4d801d02cbf3498390727. Returning it.\n",
      "Cached result found for bef20208ff1950f20ffb7cc88597014e05c2b370d9d19aaaa6fe17077bc7f4fb. Returning it.\n",
      "Cached result found for 3689681305175dea1e64a3037dbe5ea8208e19362cae8f34fe7dbf6ebaff65b7. Returning it.\n",
      "Cached result found for 1bc0e9bea1f3cfda2dd8a7dd4bfa324bcd487d7533c69fd31e1477a8bfcf422e. Returning it.\n",
      "Cached result found for 5a96cec7062be87aea7e40b8d30735d12437647f2fe95c120df4d6c07ac52b10. Returning it.\n",
      "Cached result found for bb4b8f8f13096b02130ce441720eac303b6c0652cf2684391b9b9d88ce31293f. Returning it.\n",
      "Cached result found for 637557a6c6cddeb9233334b1d702811a37ab137335e0bc6a3e8480a156ad81bc. Returning it.\n",
      "Cached result found for 29969bbddbf8c9097626e92ddf37279920a94ff06e61a70dff819034868d50ff. Returning it.\n",
      "Cached result found for b0e7706683a81ce62e3267405076894fe1b7be88216034e782daa43e077a9f89. Returning it.\n",
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      "Cached result found for 0609495231fdd2983b92fd7e8eec6a40c115ace65c5b67a00ffa2087012caf9c. Returning it.\n",
      "Cached result found for 9fec1a59e8d0251de2fa0ddf8e19c799de6d9dd61c1bea0bf3ca26bd03402055. Returning it.\n",
      "Cached result found for 8924b1424f939296ac2243607d111f3c382904262a16eea33e57af8780efb748. Returning it.\n",
      "Cached result found for 23e4b22d799aad558ee6a621eb890392659f760bc13c6e72bac456637a3998c7. Returning it.\n",
      "Cached result found for 339147af60d2d922d6d6678ad9dfb7fe5d035127de49bbefb4f5ab0d322b2677. Returning it.\n",
      "Cached result found for 14da3510ff69a1621c2458df7d4b81cfcc86be112537015bbfa38b1aba7c0dd3. Returning it.\n",
      "Cached result found for 030018890d50aebd62363c0064a26d88f293ce5956474b59893efc4966aa7c61. Returning it.\n",
      "Cached result found for 7b307dc76e9c847dd6e9d6f47557df9f5b32d9aa664e3d5fc81d2d741a01c902. Returning it.\n",
      "Cached result found for d5f9ded695b9bc10875bf0f70e0b11d863676f6e48999cd08d21312116be65a7. Returning it.\n",
      "Cached result found for 1b42c4f05cb9e0f25639787692bc72e7fbf323e30d883e6c6bb05fcffa4e750b. Returning it.\n",
      "Cached result found for 4f4639a468a2a24093cdc796856903bf6f707b0e04d4be0fbf9ba5937d196274. Returning it.\n",
      "Cached result found for 3cb3dd08f7f57eeb8276c65104b278c769feee5371624726137d8714c7de63dd. Returning it.\n",
      "Cached result found for 0984b531264a1f4c126c9d81276e0397b39f69f2fe181e4e84a041a75c089cb5. Returning it.\n",
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      "Cached result found for 797a37cb09cf9483c41685fbc516ef6c6b2a8aca75b0a0ebcb421384d8565045. Returning it.\n",
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      "Cached result found for 2aad8b6117c888e22baf8c53aab60b691f369bb6c3adcf9d970d14f8a6b60e5c. Returning it.\n"
     ]
    }
   ],
   "source": [
    "embeddings: Dict[Section, List[float]] = {\n",
    "    section: get_embedding(str(section)) for section in sections\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c84abbd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_messages(context: List[Section], question: str) -> List[Dict[str, str]]:\n",
    "    context_str = \"\\n\\n\".join([f\"Path: {x.location}\\nBody:\\n{x.text}\" for x in context])\n",
    "    return [\n",
    "        {\"role\": \"system\", \"content\": \"\"\"\n",
    "You will receive a question from the user and some context to help you answer the question.\n",
    "\n",
    "Evaluate the context and provide an answer if you can confidently answer the question.\n",
    "\n",
    "If you are unable to provide a confident response, kindly state that it is the case and explain the reason.\n",
    "\n",
    "Prioritize offering an \"I don't know\" response over conveying potentially false information.\n",
    "\n",
    "The user will only see your response and not the context you've been provided. Thus, respond in precise detail, directly repeating the information that you're referencing from the context.\n",
    "\"\"\".strip()},\n",
    "        {\"role\": \"user\", \"content\": f\"\"\"\n",
    "Using the following information as context, I'd like you to answer a question.\n",
    "\n",
    "{context_str}\n",
    "\n",
    "Please answer the following question: {question}\n",
    "\"\"\".strip()}\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "506db5d9",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing embedding for Who came in 2nd at the British Grand Prix in 2022\n",
      "Using 5 documents as context:\n",
      "2022 British Grand Prix - 2022 British Grand Prix: 0.8783113848409239\n",
      "2022 British Grand Prix - Race - 2022 British Grand Prix - Race: 0.8599746130838734\n",
      "2022 British Grand Prix - See also: 0.8570878054062624\n",
      "2022 British Grand Prix - References: 0.8569848634313646\n",
      "2022 Italian Grand Prix - 2022 Italian Grand Prix: 0.853530327807686\n",
      "Prompt: Using the following Markdown document as context, I'd like you to answer a question.\n",
      "\n",
      "Path: 2022 British Grand Prix - 2022 British Grand Prix\n",
      "Body:\n",
      "The 2022 British Grand Prix (officially known as the Formula 1 Lenovo British Grand Prix 2022) was a Formula One motor race held on 3 July 2022 at the Silverstone Circuit in Northamptonshire, England.\n",
      "Carlos Sainz Jr. took both his first pole position and Formula One victory, ahead of Sergio Pérez and Lewis Hamilton. Championship leader, Max Verstappen finished seventh after acquiring car damage early in the race. A multi-car crash occurred on the opening lap, in which Zhou Guanyu's car flipped over the tyre wall marking the circuit boundaries.\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 British Grand Prix - Race - 2022 British Grand Prix - Race\n",
      "Body:\n",
      "Race ==\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 British Grand Prix - See also\n",
      "Body:\n",
      "2022 British Grand Prix: See also ==\n",
      "2022 Silverstone Formula 2 round\n",
      "2022 Silverstone Formula 3 round\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 British Grand Prix - References\n",
      "Body:\n",
      "2022 British Grand Prix: References ==\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 Italian Grand Prix - 2022 Italian Grand Prix\n",
      "Body:\n",
      "The 2022 Italian Grand Prix (officially known as the Formula 1 Pirelli Gran Premio d'Italia 2022) was a Formula One motor race held on 11 September 2022 at the Monza Circuit in Monza, Italy. Daniel Ricciardo entered the race as the defending winner, having won the previous Italian Grand Prix. The race finished with a controversial safety car period and was won by Max Verstappen, with Charles Leclerc and George Russell taking second and third place respectively. Nyck de Vries scored points with a ninth place finish on his debut.\n",
      "\n",
      "\n",
      "\n",
      "Please answer the following question: Who came in 2nd at the British Grand Prix in 2022\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'According to the provided context, Sergio Pérez came in 2nd at the British Grand Prix in 2022.'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ask_embedding_store(\"Who came in 2nd at the British Grand Prix in 2022\", embeddings, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "ba262cc1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing embedding for Who won the 2022 Monaco f1 Grand Prix?\n",
      "Using 5 documents as context:\n",
      "2022 Monaco Grand Prix - 2022 Monaco Grand Prix: 0.8894262198166776\n",
      "2022 Italian Grand Prix - 2022 Italian Grand Prix: 0.8719332260066504\n",
      "2022 French Grand Prix - 2022 French Grand Prix: 0.8716700939202514\n",
      "2022 Canadian Grand Prix - 2022 Canadian Grand Prix: 0.8689576327657613\n",
      "2022 Spanish Grand Prix - 2022 Spanish Grand Prix: 0.867726743268248\n",
      "Prompt: Using the following Markdown document as context, I'd like you to answer a question.\n",
      "\n",
      "Path: 2022 Monaco Grand Prix - 2022 Monaco Grand Prix\n",
      "Body:\n",
      "The 2022 Monaco Grand Prix (officially known as the Formula 1 Grand Prix de Monaco 2022) was a Formula One motor race held on 29 May 2022 at the Circuit de Monaco in the Principality of Monaco. It was round 7 of 22 in the 2022 Formula One World Championship.Charles Leclerc took pole in front of Carlos Sainz Jr. and Sergio Pérez. The race started with a rolling start after a 65-minute delay. Leclerc lost the race lead to strategy error and dropped down to fourth place behind Max Verstappen and Sainz, as Pérez won the race.\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 Italian Grand Prix - 2022 Italian Grand Prix\n",
      "Body:\n",
      "The 2022 Italian Grand Prix (officially known as the Formula 1 Pirelli Gran Premio d'Italia 2022) was a Formula One motor race held on 11 September 2022 at the Monza Circuit in Monza, Italy. Daniel Ricciardo entered the race as the defending winner, having won the previous Italian Grand Prix. The race finished with a controversial safety car period and was won by Max Verstappen, with Charles Leclerc and George Russell taking second and third place respectively. Nyck de Vries scored points with a ninth place finish on his debut.\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 French Grand Prix - 2022 French Grand Prix\n",
      "Body:\n",
      "The 2022 French Grand Prix (officially known as the Formula 1 Lenovo Grand Prix de France 2022) was a Formula One motor race held on 24 July 2022 at the Circuit Paul Ricard in Le Castellet, France.\n",
      "Going into the race with 2 consecutive wins for Ferrari and a solid qualifying performance that saw him in pole position, championship challenger Charles Leclerc and Ferrari were favoured for the win, which would have reduced their arrears to the championship leader and title holder Max Verstappen. However, Leclerc, who had been leading the race, spun out on lap 18, gifting the win to Verstappen. Mercedes drivers Lewis Hamilton and George Russell finished second and third, respectively, giving the team their first double podium of the season. \n",
      "The race was arguably a turning point in the season, as Verstappen and Red Bull powered on to a streak of victories that saw them become Champions, whilst Ferrari never recovered from the points and pace deficit that arose over the remainder of the season, a fact highlighted by the Monegasque driver's scream of despair and frustration after crashing out.\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 Canadian Grand Prix - 2022 Canadian Grand Prix\n",
      "Body:\n",
      "The 2022 Canadian Grand Prix (officially known as the Formula 1 AWS Grand Prix du Canada 2022) was a Formula One motor race, which was held on 19 June 2022 at the Circuit Gilles Villeneuve in Montreal, Quebec, Canada. It was the 9th round of the 2022 Formula One World Championship.\n",
      "Max Verstappen took pole position, in a rain affected qualifying, from Fernando Alonso and Carlos Sainz Jr. Verstappen converted his pole into victory, ahead of Sainz and Lewis Hamilton.\n",
      "\n",
      "\n",
      "\n",
      "Path: 2022 Spanish Grand Prix - 2022 Spanish Grand Prix\n",
      "Body:\n",
      "The 2022 Spanish Grand Prix (officially known as the Formula 1 Pirelli Gran Premio de España 2022) was a Formula One motor race held on 22 May 2022 at the Circuit de Barcelona-Catalunya in Montmeló, Spain. It was the 62nd edition of the Spanish Grand Prix and the sixth round of the 2022 Formula One World Championship.Max Verstappen won the race ahead of teammate Sergio Pérez, while George Russell completed the podium. Charles Leclerc, the pole-sitter and championship leader, was forced to retire due to engine issues. Leclerc's teammate Carlos Sainz Jr. recovered from 11th, after suffering a spin, to finish fourth, ahead of Lewis Hamilton, who also made a come back from 19th, after suffering a puncture at the start. With the win, Red Bull led Ferrari in the Constructors' Championship, while the Drivers' Championship standings switched from a 19-point Leclerc lead to a 6-point advantage for Verstappen.\n",
      "\n",
      "\n",
      "\n",
      "Please answer the following question: Who won the 2022 Monaco f1 Grand Prix?\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Pérez won the 2022 Monaco Grand Prix.'"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ask_embedding_store(\"Who won the 2022 Monaco f1 Grand Prix?\", embeddings, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "29e271f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cached result found for f8ff0cd014ee197988ef8c19e7539c0046fc42b228c2bed826254a697e08a935. Returning it.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\"A multi-car crash occurred on the opening lap of the 2022 British Grand Prix, in which Zhou Guanyu's car flipped over the tyre wall marking the circuit boundaries. Gasly attempted to pass between Zhou and Russell, but Russell moved to the left too late to close the gap causing his left rear tyre to make contact with Gasly's right front. Gasly backed out but the impact pointed Russell's car to the left shooting him across the track and directly into the side of Zhou's car. The impact launched Zhou's car into the air. He landed upside down, skidding down the track, then skipping and bouncing across the long gravel trap at the end of the straightaway, all while barely slowing and turning sideways. The inverted car suddenly dug into the gravel carrying sufficient speed and momentum to launch it over the tire barrier, rotating 540 degrees on its axis before hitting the catch fencing sideways facing up just a few feet from the front row of the grandstand. It then dropped 8 feet and landed wedged into the small gap between the fence and tire barrier, stopping on its side with the cockpit up against the backside of the tire barrier. Valtteri Bottas slowed slightly, which caused Alexander Albon to also slow. Sebastian Vettel attempted to brake, but was too close to Albon and hit him. Albon spun into the concrete pit wall, rebounded back on the track, and was hit by Yuki Tsunoda and Esteban Ocon, damaging both of their cars.\""
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ask_embedding_store(\"What happened in the first lap of the 2022 British Grand Prix?\", embeddings, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "787437af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cached result found for 68ae105f227607f5a2f32fbc816df92992a1a888c5bb7fd311a5226aaea829fb. Returning it.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Daniel Ricciardo finished 9th in the French Grand Prix in 2022.'"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ask_embedding_store(\"Who finished 9th in the French Grand Prix in 2022?\", embeddings, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "fea90f47",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cached result found for ebdb78c0f0c96823c004debcc609edb2ad8a6cace05f1d1a738e363b5bd2c4a4. Returning it.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'Max Verstappen won the F1 drivers championship in 2022, his second world championship title. This is stated in the following section from the context: \"Max Verstappen, who was the reigning Drivers\\' Champion, claimed his second title at the Japanese Grand Prix.\"'"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ask_embedding_store(\"Who won the F1 drivers championship in 2022?\", embeddings, 5)"
   ]
  }
 ],
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