lab8/VertexAI_LangChain_Redis.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/gmflau/google-dev-day-workshop/blob/main/lab8/VertexAI_LangChain_Redis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R2-i8jBl9GRH"
      },
      "source": [
        "# Document Question Answering with Langchain, VertexAI and Redis\n",
        "\n",
        "![Redis](https://redis.com/wp-content/themes/wpx/assets/images/logo-redis.svg?auto=webp&quality=85,75&width=120)\n",
        "\n",
        "This notebook would use your own deployment of VertexAI, Redis with Vector Similarity Search and Langchain to answer guestions about the information contained in a document.\n",
        "\n",
        "<img src=\"https://drive.google.com/uc?id=1cWQsP_onUpDX5tBB66_ZX3e6_Rbm8kWm\" height=\"80%\" width=\"80%\">"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RZsd9twK9-sJ"
      },
      "source": [
        "### Install Dependencies\n",
        "\n",
        "WARNING!!! We have to downgrade the version of one of the libraries here and that requires restart of the notebook runtime. At the end of the next cell you'll be prompted to restart the runtime. Restart and continue with the execution."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "C8uONNrVbe08",
        "outputId": "ca9d7357-3bb7-47b6-9a93-b3c43bc251c0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting redis\n",
            "  Downloading redis-4.6.0-py3-none-any.whl (241 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m241.1/241.1 kB\u001b[0m \u001b[31m6.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting langchain\n",
            "  Downloading langchain-0.0.216-py3-none-any.whl (1.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m18.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting tiktoken\n",
            "  Downloading tiktoken-0.4.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.7 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.7/1.7 MB\u001b[0m \u001b[31m36.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting google-cloud-aiplatform\n",
            "  Downloading google_cloud_aiplatform-1.26.1-py2.py3-none-any.whl (2.6 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.6/2.6 MB\u001b[0m \u001b[31m38.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting shapely<2.0.0\n",
            "  Downloading Shapely-1.8.5.post1-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m50.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting wget\n",
            "  Downloading wget-3.2.zip (10 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: async-timeout>=4.0.2 in /usr/local/lib/python3.10/dist-packages (from redis) (4.0.2)\n",
            "Requirement already satisfied: PyYAML>=5.4.1 in /usr/local/lib/python3.10/dist-packages (from langchain) (6.0)\n",
            "Requirement already satisfied: SQLAlchemy<3,>=1.4 in /usr/local/lib/python3.10/dist-packages (from langchain) (2.0.16)\n",
            "Requirement already satisfied: aiohttp<4.0.0,>=3.8.3 in /usr/local/lib/python3.10/dist-packages (from langchain) (3.8.4)\n",
            "Collecting dataclasses-json<0.6.0,>=0.5.7 (from langchain)\n",
            "  Downloading dataclasses_json-0.5.8-py3-none-any.whl (26 kB)\n",
            "Collecting langchainplus-sdk>=0.0.17 (from langchain)\n",
            "  Downloading langchainplus_sdk-0.0.17-py3-none-any.whl (25 kB)\n",
            "Requirement already satisfied: numexpr<3.0.0,>=2.8.4 in /usr/local/lib/python3.10/dist-packages (from langchain) (2.8.4)\n",
            "Requirement already satisfied: numpy<2,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain) (1.22.4)\n",
            "Collecting openapi-schema-pydantic<2.0,>=1.2 (from langchain)\n",
            "  Downloading openapi_schema_pydantic-1.2.4-py3-none-any.whl (90 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m90.0/90.0 kB\u001b[0m \u001b[31m9.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: pydantic<2,>=1 in /usr/local/lib/python3.10/dist-packages (from langchain) (1.10.9)\n",
            "Requirement already satisfied: requests<3,>=2 in /usr/local/lib/python3.10/dist-packages (from langchain) (2.27.1)\n",
            "Requirement already satisfied: tenacity<9.0.0,>=8.1.0 in /usr/local/lib/python3.10/dist-packages (from langchain) (8.2.2)\n",
            "Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken) (2022.10.31)\n",
            "Requirement already satisfied: google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0 in /usr/local/lib/python3.10/dist-packages (from google-cloud-aiplatform) (2.11.1)\n",
            "Requirement already satisfied: proto-plus<2.0.0dev,>=1.22.0 in /usr/local/lib/python3.10/dist-packages (from google-cloud-aiplatform) (1.22.3)\n",
            "Requirement already satisfied: protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.19.5 in /usr/local/lib/python3.10/dist-packages (from google-cloud-aiplatform) (3.20.3)\n",
            "Requirement already satisfied: packaging>=14.3 in /usr/local/lib/python3.10/dist-packages (from google-cloud-aiplatform) (23.1)\n",
            "Requirement already satisfied: google-cloud-storage<3.0.0dev,>=1.32.0 in /usr/local/lib/python3.10/dist-packages (from google-cloud-aiplatform) (2.8.0)\n",
            "Requirement already satisfied: google-cloud-bigquery<4.0.0dev,>=1.15.0 in /usr/local/lib/python3.10/dist-packages (from google-cloud-aiplatform) (3.10.0)\n",
            "Collecting google-cloud-resource-manager<3.0.0dev,>=1.3.3 (from google-cloud-aiplatform)\n",
            "  Downloading google_cloud_resource_manager-1.10.1-py2.py3-none-any.whl (321 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m321.3/321.3 kB\u001b[0m \u001b[31m13.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (23.1.0)\n",
            "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (2.0.12)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (6.0.4)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.9.2)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.3.3)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp<4.0.0,>=3.8.3->langchain) (1.3.1)\n",
            "Collecting marshmallow<4.0.0,>=3.3.0 (from dataclasses-json<0.6.0,>=0.5.7->langchain)\n",
            "  Downloading marshmallow-3.19.0-py3-none-any.whl (49 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m49.1/49.1 kB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting marshmallow-enum<2.0.0,>=1.5.1 (from dataclasses-json<0.6.0,>=0.5.7->langchain)\n",
            "  Downloading marshmallow_enum-1.5.1-py2.py3-none-any.whl (4.2 kB)\n",
            "Collecting typing-inspect>=0.4.0 (from dataclasses-json<0.6.0,>=0.5.7->langchain)\n",
            "  Downloading typing_inspect-0.9.0-py3-none-any.whl (8.8 kB)\n",
            "Requirement already satisfied: googleapis-common-protos<2.0.dev0,>=1.56.2 in /usr/local/lib/python3.10/dist-packages (from google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (1.59.1)\n",
            "Requirement already satisfied: google-auth<3.0.dev0,>=2.14.1 in /usr/local/lib/python3.10/dist-packages (from google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (2.17.3)\n",
            "Requirement already satisfied: grpcio<2.0dev,>=1.33.2 in /usr/local/lib/python3.10/dist-packages (from google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (1.56.0)\n",
            "Requirement already satisfied: grpcio-status<2.0.dev0,>=1.33.2 in /usr/local/lib/python3.10/dist-packages (from google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (1.48.2)\n",
            "Requirement already satisfied: google-cloud-core<3.0.0dev,>=1.6.0 in /usr/local/lib/python3.10/dist-packages (from google-cloud-bigquery<4.0.0dev,>=1.15.0->google-cloud-aiplatform) (2.3.2)\n",
            "Requirement already satisfied: google-resumable-media<3.0dev,>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from google-cloud-bigquery<4.0.0dev,>=1.15.0->google-cloud-aiplatform) (2.5.0)\n",
            "Requirement already satisfied: python-dateutil<3.0dev,>=2.7.2 in /usr/local/lib/python3.10/dist-packages (from google-cloud-bigquery<4.0.0dev,>=1.15.0->google-cloud-aiplatform) (2.8.2)\n",
            "Requirement already satisfied: grpc-google-iam-v1<1.0.0dev,>=0.12.4 in /usr/local/lib/python3.10/dist-packages (from google-cloud-resource-manager<3.0.0dev,>=1.3.3->google-cloud-aiplatform) (0.12.6)\n",
            "Requirement already satisfied: typing-extensions>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<2,>=1->langchain) (4.6.3)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (1.26.16)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (2023.5.7)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3,>=2->langchain) (3.4)\n",
            "Requirement already satisfied: greenlet!=0.4.17 in /usr/local/lib/python3.10/dist-packages (from SQLAlchemy<3,>=1.4->langchain) (2.0.2)\n",
            "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3.0.dev0,>=2.14.1->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (5.3.1)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3.0.dev0,>=2.14.1->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (0.3.0)\n",
            "Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3.0.dev0,>=2.14.1->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (1.16.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3.0.dev0,>=2.14.1->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (4.9)\n",
            "Requirement already satisfied: google-crc32c<2.0dev,>=1.0 in /usr/local/lib/python3.10/dist-packages (from google-resumable-media<3.0dev,>=0.6.0->google-cloud-bigquery<4.0.0dev,>=1.15.0->google-cloud-aiplatform) (1.5.0)\n",
            "Collecting mypy-extensions>=0.3.0 (from typing-inspect>=0.4.0->dataclasses-json<0.6.0,>=0.5.7->langchain)\n",
            "  Downloading mypy_extensions-1.0.0-py3-none-any.whl (4.7 kB)\n",
            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3.0.dev0,>=2.14.1->google-api-core[grpc]!=2.0.*,!=2.1.*,!=2.2.*,!=2.3.*,!=2.4.*,!=2.5.*,!=2.6.*,!=2.7.*,<3.0.0dev,>=1.32.0->google-cloud-aiplatform) (0.5.0)\n",
            "Building wheels for collected packages: wget\n",
            "  Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for wget: filename=wget-3.2-py3-none-any.whl size=9657 sha256=4006a24e4abe0527543ac4dcae388e2e13e34af34c56a4a4a62a1c9badc1878d\n",
            "  Stored in directory: /root/.cache/pip/wheels/8b/f1/7f/5c94f0a7a505ca1c81cd1d9208ae2064675d97582078e6c769\n",
            "Successfully built wget\n",
            "Installing collected packages: wget, shapely, redis, mypy-extensions, marshmallow, typing-inspect, tiktoken, openapi-schema-pydantic, marshmallow-enum, langchainplus-sdk, dataclasses-json, langchain, google-cloud-resource-manager, google-cloud-aiplatform\n",
            "  Attempting uninstall: shapely\n",
            "    Found existing installation: shapely 2.0.1\n",
            "    Uninstalling shapely-2.0.1:\n",
            "      Successfully uninstalled shapely-2.0.1\n",
            "Successfully installed dataclasses-json-0.5.8 google-cloud-aiplatform-1.26.1 google-cloud-resource-manager-1.10.1 langchain-0.0.216 langchainplus-sdk-0.0.17 marshmallow-3.19.0 marshmallow-enum-1.5.1 mypy-extensions-1.0.0 openapi-schema-pydantic-1.2.4 redis-4.6.0 shapely-1.8.5.post1 tiktoken-0.4.0 typing-inspect-0.9.0 wget-3.2\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "google"
                ]
              }
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "!pip install redis \"langchain==0.0.227\" tiktoken \"google-cloud-aiplatform==1.25.0\" 'shapely<2.0.0' wget\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NXTpvvXi_Lfe"
      },
      "source": [
        "WARNING!!! If prompted to restart the runtime in the cell ^^above^^ - agree and rerun the cells"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TL1elOT86L2D"
      },
      "source": [
        "### Authenticate notebook to Google Cloud\n",
        "\n",
        "The code below will ask you to Allow this notebook to access your Google credentials. Agree, select the email address associated with your GCP account and click `Allow`.\n",
        "\n",
        "You might also need to enable VertexAI API in your Google Gloud account and change project name and the region."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7dugRi01g7Gb"
      },
      "outputs": [],
      "source": [
        "#Connect notebook to your google cloud account\n",
        "from google.colab import auth as google_auth\n",
        "from google.cloud import aiplatform\n",
        "#replace values below with your own Project and GCP Region\n",
        "PROJECT_ID = \"redis-business-development\"\n",
        "REGION = \"us-central1\"\n",
        "google_auth.authenticate_user()\n",
        "aiplatform.init(project=PROJECT_ID, location=REGION)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NBlbUrB27QQs"
      },
      "source": [
        "### Install Redis Stack\n",
        "\n",
        "Redis will be used as Vector Similarity Search engine for Langchain. Instead of using in-notebook Redis Stack you can provision your own free instance of Redis in the cloud. Get your own Free Redis Cloud instance at https://redis.com/try-free/"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aKMKXPY2j8Gt",
        "outputId": "40ade886-7fe2-44f4-ea44-83640d06bf41"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "deb [signed-by=/usr/share/keyrings/redis-archive-keyring.gpg] https://packages.redis.io/deb focal main\n",
            "Starting redis-stack-server, database path /var/lib/redis-stack\n"
          ]
        }
      ],
      "source": [
        "%%sh\n",
        "curl -fsSL https://packages.redis.io/gpg | sudo gpg --dearmor -o /usr/share/keyrings/redis-archive-keyring.gpg\n",
        "echo \"deb [signed-by=/usr/share/keyrings/redis-archive-keyring.gpg] https://packages.redis.io/deb $(lsb_release -cs) main\" | sudo tee /etc/apt/sources.list.d/redis.list\n",
        "sudo apt-get update  > /dev/null 2>&1\n",
        "sudo apt-get install redis-stack-server  > /dev/null 2>&1\n",
        "redis-stack-server --daemonize yes"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "X7UsU1Ts7TUL"
      },
      "source": [
        "### Connect to Redis\n",
        "\n",
        "By default this notebook would connect to the local instance of Redis Stack. If you have your own Redis Cloud instance - replace REDIS_PASSWORD, REDIS_HOST and REDIS_PORT values with your own."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dyPfCO3pkB7M"
      },
      "outputs": [],
      "source": [
        "import redis\n",
        "import os\n",
        "\n",
        "\n",
        "REDIS_HOST = os.getenv(\"REDIS_HOST\", \"localhost\")\n",
        "REDIS_PORT = os.getenv(\"REDIS_PORT\", \"6379\")\n",
        "REDIS_PASSWORD = os.getenv(\"REDIS_PASSWORD\", \"\")\n",
        "#Replace values above with your own if using Redis Cloud instance\n",
        "#REDIS_HOST=\"redis-18374.c253.us-central1-1.gce.cloud.redislabs.com\"\n",
        "#REDIS_PORT=18374\n",
        "#REDIS_PASSWORD=\"1TNxTEdYRDgIDKM2gDfasupCADXXXX\"\n",
        "\n",
        "#shortcut for redis-cli $REDIS_CONN command\n",
        "if REDIS_PASSWORD!=\"\":\n",
        "  os.environ[\"REDIS_CONN\"]=f\"-h {REDIS_HOST} -p {REDIS_PORT} -a {REDIS_PASSWORD} --no-auth-warning\"\n",
        "else:\n",
        "  os.environ[\"REDIS_CONN\"]=f\"-h {REDIS_HOST} -p {REDIS_PORT}\"\n",
        "\n",
        "REDIS_URL = f\"redis://:{REDIS_PASSWORD}@{REDIS_HOST}:{REDIS_PORT}\"\n",
        "INDEX_NAME = f\"qna:idx\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_h1e-L9yZfaY"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "import wget\n",
        "from langchain.embeddings.vertexai import VertexAIEmbeddings\n",
        "from langchain.vectorstores.redis import Redis\n",
        "from langchain.text_splitter import CharacterTextSplitter\n",
        "from langchain.llms import VertexAI\n",
        "from langchain.chains import RetrievalQA"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "9XL4P-k1d0Pi",
        "outputId": "309c8ca6-55db-4600-9aab-c4f23554b1fd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'state_of_the_union.txt'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ],
      "source": [
        "#!wget https://raw.githubusercontent.com/hwchase17/chat-your-data/master/state_of_the_union.txt\n",
        "wget.download(\"https://raw.githubusercontent.com/hwchase17/chat-your-data/master/state_of_the_union.txt\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KXDbABtw-vAQ"
      },
      "source": [
        "### Load text and split it into managable chunks\n",
        "\n",
        "Without this step any large body of text would exceed the limit of tokens you can feed to the LLM"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4zfOlQeeZjsN"
      },
      "outputs": [],
      "source": [
        "from langchain.document_loaders import TextLoader\n",
        "loader = TextLoader(\"./state_of_the_union.txt\")\n",
        "documents = loader.load()\n",
        "text_splitter = CharacterTextSplitter(chunk_size=500, chunk_overlap=30)\n",
        "texts = text_splitter.split_documents(documents)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Dv1JVm31_OF9"
      },
      "source": [
        "### Initialize embeddings engine\n",
        "\n",
        "Here we are using VertexAI embeddings engine."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gaJrhuKa_Mwt"
      },
      "outputs": [],
      "source": [
        "embeddings = VertexAIEmbeddings()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6zgvqB6wCJWK"
      },
      "source": [
        "### Initialize LLM\n",
        "\n",
        "In this notebook we are using VertexAI from Google Cloud."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "iQRyyWU0CNbJ"
      },
      "outputs": [],
      "source": [
        "llm = VertexAI()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qrj-jeGmBRTL"
      },
      "source": [
        "### Create vector store from the documents using Redis as Vector Database"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yY69FViAjNv1"
      },
      "outputs": [],
      "source": [
        "def get_vectorstore() -> Redis:\n",
        "    \"\"\"Create the Redis vectorstore.\"\"\"\n",
        "\n",
        "    try:\n",
        "        vectorstore = Redis.from_existing_index(\n",
        "            embedding=embeddings,\n",
        "            index_name=INDEX_NAME,\n",
        "            redis_url=REDIS_URL\n",
        "        )\n",
        "        return vectorstore\n",
        "    except:\n",
        "        pass\n",
        "\n",
        "    # Load Redis with documents\n",
        "    vectorstore = Redis.from_documents(\n",
        "        documents=texts,\n",
        "        embedding=embeddings,\n",
        "        index_name=INDEX_NAME,\n",
        "        redis_url=REDIS_URL\n",
        "    )\n",
        "    return vectorstore\n",
        "\n",
        "\n",
        "redis = get_vectorstore()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XdzQa112Bf2b"
      },
      "source": [
        "## Specify the prompt template\n",
        "\n",
        "PromptTemplate defines the exect text of the response that would be fed to the LLM. This step is optional, but the defaults usually work well for OpenAI and might fall short for other models."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yKKn2KKp3TQ4"
      },
      "outputs": [],
      "source": [
        "def get_prompt():\n",
        "    \"\"\"Create the QA chain.\"\"\"\n",
        "    from langchain.prompts import PromptTemplate\n",
        "    from langchain.chains import RetrievalQA\n",
        "\n",
        "    # Define our prompt\n",
        "    prompt_template = \"\"\"Use the following pieces of context to answer the question at the end. If you don't know the answer, say that you don't know, don't try to make up an answer.\n",
        "\n",
        "    This should be in the following format:\n",
        "\n",
        "    Question: [question here]\n",
        "    Answer: [answer here]\n",
        "\n",
        "    Begin!\n",
        "\n",
        "    Context:\n",
        "    ---------\n",
        "    {context}\n",
        "    ---------\n",
        "    Question: {question}\n",
        "    Answer:\"\"\"\n",
        "\n",
        "    prompt = PromptTemplate(\n",
        "        template=prompt_template,\n",
        "        input_variables=[\"context\", \"question\"]\n",
        "    )\n",
        "    return prompt"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xgEXBujxG1dO"
      },
      "source": [
        "### Putting it all together\n",
        "\n",
        "This is where the Langchain brings all the components together in a form of a simple QnA chain"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RKNSP0zqZq98"
      },
      "outputs": [],
      "source": [
        "qa = RetrievalQA.from_chain_type(\n",
        "    llm=llm,\n",
        "    chain_type=\"stuff\",\n",
        "    retriever=redis.as_retriever(),\n",
        "    #return_source_documents=True,\n",
        "    chain_type_kwargs={\"prompt\": get_prompt()},\n",
        "    #verbose=True\n",
        "    )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-ox7LffJ8VNe"
      },
      "source": [
        "### Debugging Redis\n",
        "\n",
        "The code block below is exampleof how you can interact with the Redis Database"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rGH8mdG2na0w"
      },
      "outputs": [],
      "source": [
        "#!redis-cli $REDIS_CONN keys \"*\"\n",
        "#!redis-cli $REDIS_CONN HGETALL \"doc:qna:idx:2005b093c6af4f6c899779802910ed69\"\n",
        "\n",
        "###-- FLUSHDB will wipe out the entire database!!! Use with caution --###\n",
        "#!redis-cli $REDIS_CONN flushdb\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SURTtVbYBFGc"
      },
      "source": [
        "## Finally - let's ask questions!\n",
        "\n",
        "Examples:\n",
        "- What did the president say about Kentaji Brown Jackson\n",
        "- Did he mention Stephen Breyer?\n",
        "- What was his stance on Ukraine"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "0JkswfOHZu9h",
        "outputId": "71a6ae1b-4fb5-4ac6-e9b8-a92d5ef97a31"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 29
        }
      ],
      "source": [
        "\n",
        "\n",
        "query = \"What did the president say about Kentaji Brown Jackson\"\n",
        "qa.run(query)"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}