MDBLoad-SM-Deming.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 38670,
     "status": "ok",
     "timestamp": 1705687956904,
     "user": {
      "displayName": "John Willis",
      "userId": "15271974867993570949"
     },
     "user_tz": 360
    },
    "id": "KeIAv4AWCwop",
    "outputId": "b8cbd7fa-a8f7-40d7-f583-85c17c7a9cd9"
   },
   "outputs": [
    {
     "name": "stdout",
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     "text": [
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m802.4/802.4 kB\u001b[0m \u001b[31m1.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m228.7/228.7 kB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m222.3/222.3 kB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.4/49.4 kB\u001b[0m \u001b[31m1.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.9/75.9 kB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m76.9/76.9 kB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m1.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25h\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "llmx 0.0.15a0 requires cohere, which is not installed.\n",
      "tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.9.0 which is incompatible.\u001b[0m\u001b[31m\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "%pip install --quiet langchain pypdf pymongo langchain-openai tiktoken"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 6261,
     "status": "ok",
     "timestamp": 1705688038179,
     "user": {
      "displayName": "John Willis",
      "userId": "15271974867993570949"
     },
     "user_tz": 360
    },
    "id": "qianBJwuzkeL",
    "outputId": "8463d1b8-9fb9-4b3e-fbee-2a5a7bd7ca66"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Name: langchain\n",
      "Version: 0.1.1\n",
      "Summary: Building applications with LLMs through composability\n",
      "Home-page: https://github.com/langchain-ai/langchain\n",
      "Author: \n",
      "Author-email: \n",
      "License: MIT\n",
      "Location: /usr/local/lib/python3.10/dist-packages\n",
      "Requires: aiohttp, async-timeout, dataclasses-json, jsonpatch, langchain-community, langchain-core, langsmith, numpy, pydantic, PyYAML, requests, SQLAlchemy, tenacity\n",
      "Required-by: \n",
      "3.10.12\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "%pip show langchain\n",
    "\n",
    "from platform import python_version\n",
    "print(python_version())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import boto3\n",
    "from botocore.exceptions import ClientError\n",
    "\n",
    "def get_secret():\n",
    "\n",
    "    secret_name = \"hackathon\"\n",
    "    region_name = \"us-east-1\"\n",
    "\n",
    "    # Create a Secrets Manager client\n",
    "    session = boto3.session.Session()\n",
    "    client = session.client(\n",
    "        service_name='secretsmanager',\n",
    "        region_name=region_name\n",
    "    )\n",
    "\n",
    "    try:\n",
    "        get_secret_value_response = client.get_secret_value(\n",
    "            SecretId=secret_name\n",
    "        )\n",
    "    except ClientError as e:\n",
    "        # For a list of exceptions thrown, see\n",
    "        # https://docs.aws.amazon.com/secretsmanager/latest/apireference/API_GetSecretValue.html\n",
    "        raise e\n",
    "\n",
    "    secret = json.loads(get_secret_value_response['SecretString'])\n",
    "    print(secret)\n",
    "    return secret"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'OPENAI_API_KEY': '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', 'MONGODB_ATLAS_CLUSTER_URI': 'mongodb+srv://john:jCHODesJeNCu99@profound.gae5roo.mongodb.net/?retryWrites=true&w=majority', 'LANGSMITH_API_KEY': 'ls__f0246d97a8fa43bd8093894e64d9d141'}\n"
     ]
    }
   ],
   "source": [
    "secret = get_secret()\n",
    "\n",
    "openai_api_key = secret[\"OPENAI_API_KEY\"]\n",
    "os.environ['OPENAI_API_KEY'] = openai_api_key\n",
    "\n",
    "MONGODB_ATLAS_CLUSTER_URI = secret[\"MONGODB_ATLAS_CLUSTER_URI\"]\n",
    "os.environ['MONGODB_ATLAS_CLUSTER_URI'] = MONGODB_ATLAS_CLUSTER_URI\n",
    "\n",
    "langsmith_api_key = secret[\"LANGSMITH_API_KEY\"]\n",
    "os.environ['LANGSMITH_API_KEY'] = langsmith_api_key\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collection(Database(MongoClient(host=['ac-whsldmk-shard-00-02.gae5roo.mongodb.net:27017', 'ac-whsldmk-shard-00-00.gae5roo.mongodb.net:27017', 'ac-whsldmk-shard-00-01.gae5roo.mongodb.net:27017'], document_class=dict, tz_aware=False, connect=True, retrywrites=True, w='majority', authsource='admin', replicaset='atlas-pzseul-shard-0', tls=True), 'Profound_DB'), 'Deming')\n"
     ]
    }
   ],
   "source": [
    "from pymongo import MongoClient\n",
    "\n",
    "# initialize MongoDB python client\n",
    "client = MongoClient(MONGODB_ATLAS_CLUSTER_URI)\n",
    "\n",
    "DB_NAME = \"Profound_DB\"\n",
    "COLLECTION_NAME = \"Deming\"\n",
    "ATLAS_VECTOR_SEARCH_INDEX_NAME = \"vector_index\"\n",
    "\n",
    "MONGODB_COLLECTION = client[DB_NAME][COLLECTION_NAME]\n",
    "\n",
    "print(MONGODB_COLLECTION)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "m1GSMqJL4Z7G"
   },
   "source": [
    "Now we will setup the environment variables for the MongoDB Atlas cluster\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "DpvqoXey5Gi2"
   },
   "source": [
    " In the below example, embedding is the name of the field that contains the embedding vector. Please refer to the documentation to get more details on how to define an Atlas Vector Search index. You can name the index {ATLAS_VECTOR_SEARCH_INDEX_NAME} and create the index on the namespace {DB_NAME}.{COLLECTION_NAME}. Finally, write the following definition in the JSON editor on MongoDB Atlas:\n",
    "\n",
    "~~~\n",
    "{\n",
    " \"fields\": [{\n",
    "   \"type\": \"vector\",\n",
    "   \"path\": \"embedding\",\n",
    "   \"numDimensions\": 1536,\n",
    "   \"similarity\": \"cosine\"\n",
    " }]\n",
    "}\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MElNfK8r5WWS"
   },
   "source": [
    "#Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "#loader = PyPDFLoader(\"https://arxiv.org/pdf/2303.08774.pdf\")\n",
    "loader = PyPDFLoader(\"/home/ec2-user/SageMaker/Hackathon-1-24-24/DEM.pdf\")\n",
    "data = loader.load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "id": "dOuGV0ow5clB",
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
    "\n",
    "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=150)\n",
    "docs = text_splitter.split_documents(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 96,
     "status": "ok",
     "timestamp": 1705688092655,
     "user": {
      "displayName": "John Willis",
      "userId": "15271974867993570949"
     },
     "user_tz": 360
    },
    "id": "4TxFGS535fW_",
    "outputId": "2de6bfb5-8cd0-463a-c36a-2e0b7998d098",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "page_content='hard-working grandfather? he wondered.1 When he asked his grandfather directly, \\nall Kevin got were polite deflections and a quick change of subject. The man was \\ngenerally quiet and reserved but not downright secretive.\\nThe special episode’s name didn’t help explain his grandfather’s involve-\\nment: “If Japan Can  .  .  .  Why Can’t We?” On the other hand, anyone who heard \\nthe episode’s name knew exactly what it was about: the Japanese takeover of \\nAmerican industry.\\nThe Tarnish of the Golden Age\\nWhereas the rest of the industrialized nations of the world lay in ruins after \\nWorld War II, the US was left virtually untouched. As the only game in town, \\nUS industry reigned supreme. Factories couldn’t churn out cars, radios, and \\nother manufactured goods fast enough. Quality wasn’t a concern. The only real \\nchallenge was keeping up with global demand.\\nAmerica entered what is commonly referred to as the “Golden Age* of Cap -' metadata={'source': '/home/ec2-user/SageMaker/Hackathon-1-24-24/DEM.pdf', 'page': 18}\n"
     ]
    }
   ],
   "source": [
    "print(docs[30])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "id": "JUVZbKK_5llj",
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain_community.vectorstores import MongoDBAtlasVectorSearch\n",
    "from langchain_openai import OpenAIEmbeddings\n",
    "\n",
    "# insert the documents in MongoDB Atlas with their embedding\n",
    "vector_search = MongoDBAtlasVectorSearch.from_documents(\n",
    "    documents=docs,\n",
    "    embedding=OpenAIEmbeddings(disallowed_special=()),\n",
    "    collection=MONGODB_COLLECTION,\n",
    "    index_name=ATLAS_VECTOR_SEARCH_INDEX_NAME,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 377,
     "status": "ok",
     "timestamp": 1705688109611,
     "user": {
      "displayName": "John Willis",
      "userId": "15271974867993570949"
     },
     "user_tz": 360
    },
    "id": "zfJefNOo5qxF",
    "outputId": "ffd00fc9-a2ce-48fa-ab76-db4b373b8f3a",
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Document(page_content='Part I\\nFoundations of \\nProfound Knowledge\\nTo understand the System of Profound Knowledge,  \\nwe must first look at the foundational elements  \\nthat formed Deming’s early thinking.', metadata={'_id': ObjectId('65b03db3c21c36f729c6856d'), 'embedding': [0.017061349929643945, 0.0019502911110690678, -0.0005726001958510313, -0.030889192761385298, -0.023475787243710845, 0.02739279939214625, -0.014577070381430803, -0.022161354024383503, -0.001522278562359125, -0.017560834962770243, -0.005441755688683442, 0.028391769458398847, 0.005891949545934156, -0.008267788693485514, -0.017534545590578578, 0.009293046269284731, 0.019795371994420236, -0.01895413443602753, 0.007130803148516769, -0.015746916710316604, -0.012447688044579899, -0.009858252870245145, 0.01122526390263329, -0.03659383751537277, 0.012611991964165185, 0.013762121263907238, 0.02768197503567437, -0.022200786220025956, -0.00010310089580427207, -0.004255479433500374, -0.0012174943025840934, 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Fortunately for Crawford-Mason, that one \\nclient had incredible credibility by virtue of being a high-tech manufacturing \\nFortune 500 company.', metadata={'_id': ObjectId('65b03dbec21c36f729c686e1'), 'embedding': [0.00950472532563869, -0.006017556943214194, 0.015953360293888278, -0.017944025065247088, -0.0005178183255450195, 0.014004750325152897, -0.014719708046783587, -0.013296802668615366, -0.011719691690881643, -0.02374779644353946, 0.020467402629621045, 0.01921973211497521, 0.007097002193769506, -0.022514144196434768, -0.008950984199989244, 0.024364620704446636, 0.025962760946137243, -0.003872685175306005, 0.011488381894549513, -0.028065577445760707, -0.03215905685409782, 0.0038796945419072226, -0.014348210918427098, -0.022331899267819224, -0.010829499105728568, -0.014845877111266802, 0.012175301218452747, -0.013079512071146965, -0.018252438127023263, -0.011116883834870441, 0.013969703724977455, -0.005348160453737391, -0.019654315172557182, 0.007766398217585017, 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-0.018056174930866576], 'source': '/home/ec2-user/SageMaker/Hackathon-1-24-24/DEM.pdf', 'page': 153}), Document(page_content='PART IV: THE NEXT GENERATION OF PROFOUND KNOWLEDGE\\u2009\\u2009\\u2009\\u2009\\u2009\\uf06d \\u2009\\u2009\\u2009\\u2009\\u2009\\u2009166\\nbusiness has a problem, but they’re too close to the problem to see it. It requires \\nsomeone from the outside to step in.\\nBut the beauty of Ed’s System of Profound Knowledge is that it doesn’t \\nrequire someone from the outside. It provides a way for the owners of a sys -\\ntem to bring about their own profound change, no third parties required. But \\nwhy did Ed use the metaphor of a lens to describe the System of Profound \\nKnowledge?\\nThe Perfect Picture\\nIt was indeed an iconic photograph, yet Greta never knew who kissed her.\\nGermany had already surrendered, but the war in the Pacific had dragged \\non. Even after the first atomic bomb had dropped on Hiroshima, the Japanese \\nkept fighting. Both sides knew an Allied victory was a foregone conclusion, but \\nthe last remaining Axis power was determined to fight to the bitter end. Both \\nsides prepared for a lengthy—and costly—invasion of the Japanese islands.', metadata={'_id': ObjectId('65b03dc0c21c36f729c68753'), 'embedding': [0.004729766376292275, 0.002809474464253106, -0.004097078907478448, -0.0006215727160149829, -0.0060361805086374945, 0.027482576538245377, -0.008768706541002825, -0.026921708009433255, -0.00045570599980198257, -0.029028385740279092, 0.010300836477125302, 0.029767092176517858, 0.0003434894590220946, -0.011942404265827957, -0.009247497611702384, 0.01482882716196884, 0.031299222112640336, 0.008139438888666807, 0.006764626098458976, -0.01182612584896959, -0.012113400677653841, 0.00449379112308159, 0.006935622975946146, -0.02039647651500149, 0.003960281591753227, 0.0019220020531087155, 0.028590634329958384, -0.02265363175880635, -0.0045792893289945315, -0.004449332111886214, 0.0037756054483548207, -0.003908982947602233, -0.028617994724426, -0.013173580107354949, -0.0182487591237768, -0.010109320235109992, -0.0013722479278494737, 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'/home/ec2-user/SageMaker/Hackathon-1-24-24/DEM.pdf', 'page': 191}), Document(page_content='Knowledge: a theory of psychology. In the Japanese, Ed found a culture of \\ninherent respect between manager and employee. In truth, Japan influenced \\nEd as much as Ed influenced Japan.\\nFor instance, Toyota’s world-class approach to business—called the Toyota \\nWay—is a beautiful fusion of Eastern and Western ideas, bringing together and \\nbringing out the best in both. By this time, Japan was an economic juggernaut, \\nand American businesses were eager to learn from their Eastern counterparts. \\nIn his eighties, Ed was finally getting his due.\\nJust after he passed away in 1993, Deming’s book The New Economics was \\npublished. In it, he presented his masterwork, the culmination of his life’s \\nexperiences. He brought together all four pieces of Profound Knowledge and \\nnamed it the System of Profound Knowledge (SoPK).', metadata={'_id': ObjectId('65b03db3c21c36f729c68566'), 'embedding': [0.0017911850274118259, 0.008376232314830154, 0.010838297809892618, -0.019709549436527855, -0.0051032489806387546, 0.020022192526167142, -0.002771451750033482, -0.0025695363825030066, 0.00021412803187525052, -0.03980990040679865, -0.01604901814363315, 0.009157840970250838, 0.008955925602720363, -0.0036084238008473367, -0.039366989518363406, 0.006975851615128671, 0.03217619659401488, -0.011769714340796407, -0.007536003895009264, -0.019787709743276444, -0.020347862954479504, 0.013378523611703672, 0.006601330995098441, -0.02291414250231424, 0.016921814444475495, 0.022627552227376172, 0.017976984173516238, -0.012805344924472469, 0.0011219332099259387, -0.018875833289059802, 0.006431982577266955, 0.001528206570988091, -0.006601330995098441, 0.002540226034641669, -0.018120279310985272, -0.01129423603700094, 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'/home/ec2-user/SageMaker/Hackathon-1-24-24/DEM.pdf', 'page': 23})]\n",
      "Part I\n",
      "Foundations of \n",
      "Profound Knowledge\n",
      "To understand the System of Profound Knowledge,  \n",
      "we must first look at the foundational elements  \n",
      "that formed Deming’s early thinking.\n"
     ]
    }
   ],
   "source": [
    "# Perform a similarity search between the embedding of the query and the embeddings of the documents\n",
    "query = \"Profound Knowledge\"\n",
    "results = vector_search.similarity_search(query)\n",
    "print(results)\n",
    "\n",
    "print(results[0].page_content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "6z1BxFKU5JZ5"
   },
   "outputs": [],
   "source": []
  }
 ],
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   "authorship_tag": "ABX9TyPcN4tQ1u4lkR014u0KR6Vk",
   "provenance": [
    {
     "file_id": "1bv0fjWMeMtF3f8xI0-__5mMkWEPxI605",
     "timestamp": 1705687706179
    }
   ]
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