vector_embeddings_redis.ipynb

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      "metadata": {
        "colab_type": "text",
        "id": "view-in-github"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/antonum/Redis-VSS-Streamlit/blob/main/vector_embeddings_redis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "tRlp93K0C1q8"
      },
      "source": [
        "# Vector Similarity Search with Redis\n",
        "\n",
        "[Always-on demo](https://antonum-redis-vss-streamlit-streamlit-app-p4z5th.streamlit.app/)\n",
        "\n",
        "[GitHub repo](https://github.com/antonum/Redis-VSS-Streamlit)\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 generates vector embeddings using pretrained `sentence-transformers/all-MiniLM-L6-v2` model from HuggingFace, loads them to Redis and runs Vector Similarity search against Redis database. "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H-9YfABV3_1z",
        "outputId": "379e4184-ea7c-4c59-ea47-fa8fbc22fdc8"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m240.3/240.3 kB\u001b[0m \u001b[31m17.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[?25h  Building wheel for sentence_transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ],
      "source": [
        "#install Redis client and Hugging Face sentence transformers\n",
        "!pip install -q redis sentence_transformers"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "8Nkcsc8ceWpS"
      },
      "source": [
        "Install Redis Stack locally"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nofqstGujZSE",
        "outputId": "73e1d149-eb1a-4580-a61c-ec839c0fc719"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "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 \n"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "YhS6htjOCxr_"
      },
      "source": [
        "### Connect to the Redis server"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2UxA0cSkBYgo",
        "outputId": "eda852cf-c7bc-48e3-d37d-59b7e55e935e"
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      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import os \n",
        "import redis\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-12110.c82.us-east-1-2.ec2.cloud.redislabs.com\"\n",
        "#REDIS_PORT=12110\n",
        "#REDIS_PASSWORD=\"pobhBJP7Psicp2gV0iqa2ZOc1WdXXXXX\"\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",
        "redis = redis.Redis(\n",
        "  host=REDIS_HOST,\n",
        "  port=REDIS_PORT,\n",
        "  password=REDIS_PASSWORD)\n",
        "redis.ping()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "OsJLTPAb36Z3"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sentence_transformers import SentenceTransformer\n",
        "from tqdm.auto import tqdm\n",
        "from redis import Redis\n",
        "from redis.commands.search.field import (\n",
        "    NumericField,\n",
        "    TagField,\n",
        "    TextField,\n",
        "    VectorField,\n",
        ")\n",
        "from redis.commands.search.indexDefinition import IndexDefinition, IndexType\n",
        "from redis.commands.search.query import Query\n",
        "\n",
        "\n",
        "tqdm.pandas()\n",
        "\n"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "Gz5QOrxWCFd8"
      },
      "source": [
        "### Embedding generation model\n",
        "\n",
        "Here we are using `sentence-transformers/all-MiniLM-L6-v2` from HuggingFace. https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2\n",
        "\n"
      ]
    },
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        },
        {
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              "version_major": 2,
              "version_minor": 0
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        {
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      ],
      "source": [
        "model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "hJBWKmOykJRT"
      },
      "source": [
        "Download 12k+ tweets"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yw4PTJI_Hsdn",
        "outputId": "dfc8f242-510d-4e3e-d0c3-7d39313dec4e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "--2023-06-05 16:52:47--  https://raw.githubusercontent.com/antonum/Redis-VSS-Streamlit/main/Labelled_Tweets.csv\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 2486081 (2.4M) [text/plain]\n",
            "Saving to: ‘Labelled_Tweets.csv’\n",
            "\n",
            "Labelled_Tweets.csv 100%[===================>]   2.37M  --.-KB/s    in 0.008s  \n",
            "\n",
            "2023-06-05 16:52:47 (304 MB/s) - ‘Labelled_Tweets.csv’ saved [2486081/2486081]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!wget https://raw.githubusercontent.com/antonum/Redis-VSS-Streamlit/main/Labelled_Tweets.csv"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
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        "id": "EFy8uuJH6nh3",
        "outputId": "33f1eba0-5f49-4f58-b3be-936ccf6ba2db"
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              "4          5  RT @zipillinois: 3 Surprisingly Controversial ...\n",
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        "df = pd.read_csv('Labelled_Tweets.csv').drop(columns=['created_at','score'])\n",
        "#df=df.head(3000) #trim dataframe to fit results into 30MB Redis database\n",
        "df\n"
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    {
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        "### Generate Embeddings\n",
        "\n",
        "Generate vector embeddings within the dataframe. This step can take 2-3 minutes on GPU runtime for all 12k records."
      ]
    },
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              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-326b5c19-68c4-4de8-ba73-0e8381e3e542 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-326b5c19-68c4-4de8-ba73-0e8381e3e542');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "   id                                          full_text  \\\n",
              "0   1  @KennyDegu very very little volume. With $10T ...   \n",
              "1   2  #ES_F achieved Target 2780 closing above 50% #...   \n",
              "2   3  RT @KimbleCharting: Silver/Gold indicator crea...   \n",
              "3   4  @Issaquahfunds Hedged our $MSFT position into ...   \n",
              "4   5  RT @zipillinois: 3 Surprisingly Controversial ...   \n",
              "\n",
              "                                      text_embedding  \n",
              "0  b')\\x92\\x81\\xbd\\x12h\\x8b\\xbd}\\xdf\\xe4\\xbc\\xbf\\...  \n",
              "1  b'S\\x1b\\x02\\xbd\\x16~/\\xbd\\x9bz\\xb1\\xbc`\\x99\\xd...  \n",
              "2  b'\\x0f\\xaa\\xa3\\xbdc}\\x10\\xbd\\xcc\\xe8\\xb9=(\\x08...  \n",
              "3  b'\\xc1\\x7f\\xd1\\xbc\\xbc\\n`\\xbd79 =\\xe4\\xc0\\xef=...  \n",
              "4  b'\\xca\\r\\x1e\\xbdV\\\\\\xd4\\xbcL/\\xa1\\xbc\\xe8q7=\\x...  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "def text_to_embedding(text):\n",
        "  return model.encode(text).astype(np.float32).tobytes()\n",
        "\n",
        "#generate vector embeddings\n",
        "df[\"text_embedding\"] = df[\"full_text\"].progress_apply(text_to_embedding)\n",
        "df.head()"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "E101rw12ksSa"
      },
      "source": [
        "### Create Helper Functions\n",
        " \n",
        "- Save dataframe to Redis HASH\n",
        "- Create RediSearch Index"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "HIzOD70FQOPt"
      },
      "outputs": [],
      "source": [
        "def load_dataframe(redis, df, key_prefix=\"tweet\", id_column=\"id\", pipe_size=100):\n",
        "    records = df.to_dict(orient=\"records\")\n",
        "    pipe = redis.pipeline()\n",
        "    i=1\n",
        "    for record in tqdm(records):\n",
        "        i=i+1\n",
        "        key = f\"{key_prefix}:{record[id_column]}\"\n",
        "        pipe.hset(key, mapping=record)\n",
        "        if (i+1) % pipe_size == 0:\n",
        "          res=pipe.execute()\n",
        "    pipe.execute()\n",
        "\n",
        "def create_redis_index(redis, idxname=\"tweet:idx\"):\n",
        "  try:\n",
        "    redis.ft(idxname).dropindex()\n",
        "  except:\n",
        "    print(\"no index found\")\n",
        "\n",
        "  # Create an index\n",
        "  indexDefinition = IndexDefinition(\n",
        "      prefix=[\"tweet:\"],\n",
        "      index_type=IndexType.HASH,\n",
        "  )\n",
        "\n",
        "  redis.ft(idxname).create_index(\n",
        "      (\n",
        "          TextField(\"full_text\", no_stem=False, sortable=False),\n",
        "          VectorField(\"text_embedding\", \"HNSW\", {  \"TYPE\": \"FLOAT32\", \n",
        "                                                    \"DIM\": 384, \n",
        "                                                    \"DISTANCE_METRIC\": \"COSINE\",\n",
        "                                                  })\n",
        "      ),\n",
        "      definition=indexDefinition\n",
        "  )\n",
        "\n"
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "Bpz-BT2qBqsg"
      },
      "source": [
        "### Create index and load data to Redis"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 67,
          "referenced_widgets": [
            "2defbf90932640988d0a338cdae15e4e",
            "e266844cff4241faa46cb36b9936667c",
            "870cb541b44440ad927807946025bb6a",
            "e43d000e56cb411eae7d46fc529c3b35",
            "39ca5b54e2164e14bcf3c3ba8713a449",
            "cc8d4f2b84fe49af8bd475d742e15c49",
            "4c2def9b430a4f19bd57d17492f2318f",
            "9e7f3bac76494e73b805a7b463478546",
            "087f540b1f104cfa8313962bc115e53c",
            "468406adb1cd4651ab3c979a33bdc43f",
            "dcfe1eb2c5264d99b0ba9a52c2028ea8"
          ]
        },
        "id": "i3l3Jm1KVeQq",
        "outputId": "5865c5d7-7924-4b9f-ab37-922b0981d836"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "no index found\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2defbf90932640988d0a338cdae15e4e",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "  0%|          | 0/12420 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# clear Redis database (optional)\n",
        "redis.flushdb()\n",
        "\n",
        "# create Index\n",
        "create_redis_index(redis)\n",
        "\n",
        "# load data from Dataframe to Redis HASH\n",
        "load_dataframe(redis,df,key_prefix=\"tweet\", pipe_size=100)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uXhqWfKgJqcv",
        "outputId": "81fa1f14-a34c-4bbc-9031-3982e3e29329"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "1) \"id\"\n",
            "2) \"1001\"\n",
            "3) \"text_embedding\"\n",
            "4) 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\\xbd\\xe2\\xfa\\x85\\xba\\xc7y\\x95=\\xf2\\xdf\\xa6<\\x03wF<\\a\\xd0\\x80=\\xb4\\x9a\\xca\\xbdT\\x7f\\xb2\\xbb?r\\xa3<F5\\x18=\\x0f\\xcb\\xb5=\\xcd\\xbf><\\xa4\\x88\\x8d<(#\\xee<D~c<\\n|V\\xbd\\xeddK=\\xceqB=L\\xd6\\xd6<\\xadu+\\xbd\\x9fq\\x82=/!\\xa6\\xbd\\x1eR\\xc7<Vv\\xec;\\x84\\xfd\\x99=\\xabf\\xa6\\xbc\\xd9\\xb2\\x82\\xbd@\\xeb\\xbd<\\x80\\x1f\\xac\\xbc\\xcf\\xbe\\xc0<\\xcd\\x88\\x90\\xbd\\xdc\\x7f\\xe4\\xbc\\xb8\\x0cN\\xbd\\xba\\x85\\t\\xbe?\\xee\\x93<\\xc6P0=^\\x04\\\\\\xbc\\x1aG\\x99=\\x1b8\\xb8<k\\xf6F\\xbdX\\xec\\x8d=j\\x12\\x00\\xbd\\x94\\xbd\\xc1\\xbc5\\xde\\xa2\\xbb\\xdc\\xa9D\\n\\x88\\xbf\\xdb\\xbd\\xb7Z\\x8f=\\xd1R\\x1e\\xbc\\x9eO\\xb3\\xbc\\xea\\xd2\\x85=\\xc3\\x95\\xb3=\\x040\\xe7<\\xad\\xe6\\x13<?\\xb7\\x92\\xbd\\xd2\\xb4v=\\x1b\\x9f\\xcb\\xbd\\xa3\\b\\x94=\\xb2\\x907\\xbd*q\\x1b=m6\\xf3\\xbc\\x92\\xf3\\x02\\xbewjJ=\\x0f\\x8a\\x06=|5\\xf2=MH\\xa5\\xbcg\\x7f\\x14;\\xed\\x7f*\\xbc\\xe6\\x1f\\xca<\\xad\\x1b\\xdf:\\x05g\\b\\xbc\\xa6@`<\\x1b\\xe4\\x00\\xbe3\\r]\\xbdx\\xd5\\xb4\\xbb\\xb7mt=\\\"\\x9c\\xa4;\\xdd\\xbc\\x0c=<\\xae\\xb1\\xbc\\xec\\x1b\\xf1\\xbc/\\x17\\xc9\\xbd\\xc2\\x8e\\x9e\\xbc7R\\x04\\xbd\\xc2\\xe3\\xed\\xbcM\\xc6\\xab\\xbb\\x95\\xb8\\xf6<G\\xaa\\x01\\xbd\\x16a%=\\xf48\\\\\\xbd\\xc6\\xfef\\xbd\\x9a\\x99\\x81\\xbd\\xf5\\x854:\\x8bD\\x9b\\xbc\\xcd?\\xd5<\\x98\\x13\\xa3:'\\xb4\\x0b=\\xa2$\\xdd\\xbc\\x17s\\xd1\\xbcW\\xe8\\xf8\\xbd4\\x8e\\xef;\\xef\\xbeA=\\x0b\\xce\\xc4\\xbd6\\xd6\\x8e;j{\\xa2<@\\x8e\\xa1\\xbc\\x824.=\\x00\\x13-=\\xfcNf=\\xaa*\\xa0<^@\\x13=F\\x86:\\xbd\\xed\\xac\\xf6<\\x90\\x8dI=2\\x1a\\x90<Z 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\\xbdr\\xca\\x88=k\\xd5j\\xbdR\\x8b\\x83=\\xad\\xb0\\xaa\\xbb\\xb2\\xe9g<[h\\x8e\\xbdq\\xe8[=\\xa8\\x1e\\xbd=\\x8fk\\x7f=P\\xfb\\xa5=\\xb7e\\xec\\xbc\\xfe\\x9d\\xac;\\xf88\\x92=8\\x14\\x05=8C\\xdb\\xbc\\xf8p7\\xbd\\x01\\x13\\x05=\\xdb<\\xc2<\\xae\\xf0\\xc2\\xba\\xd55\\x84;_9v=u\\x859=\\x1a2\\xe2<\\xd6\\x94\\x86\\xbc\\xc6q\\xe1\\xbb\\xfc\\xd3\\x8d\\xbd\\xb5\\xf0\\xb3=hR\\x91<`\\xd8\\xfc<\\xaa\\x91\\xa1\\xbd\\x1a\\xe6\\xac\\xbd3\\xed\\x05\\xbcE\\xf8\\xe5<\\x14*\\t\\xbdW{!=\\x12'\\xb2=pL\\xc9<\\x1f\\n\\x92<\\x19\\xefA\\xbd\\xd0\\x94\\xc1=CX\\xad\\xbd=\\x90\\x06>\\rdJ<\\xf9D\\xab\\xbd;M\\x85\\xbd\\xd9\\xfe\\a\\xbc\\x98<\\xa0=>.\\x89:?\\xa8\\xdd\\xbb\\xee\\xf9\\x01=\\xbfj\\xbc=\\xb6\\xe9\\x9c\\xbb\\xf4\\xa4\\x19=f\\x94p=\\xd07\\x97\\xbcR-\\xa0\\xb9\\\"(\\x18=\\r\\n\\x93<\\xe1\\xe2\\xfe<P\\xe4*=\\x9b\\x94\\t;F\\x9c(\\xbd'\\x17\\r\\xbc;WY=+[k<J\\x8d\\x84=D\\x87f\\xb3u\\x80\\x80\\xbdkE1<*Cw\\xbd?e\\x88=\\x85\\xc6_:\\xe6i\\x94<\\x95|h\\xbc\\xb45\\x99\\xbc!\\x1f\\xd1\\xba\\xb6\\xdb\\xad\\xbb\\x06u\\xa5=\\x0e\\x82Q\\xbdU?\\xf3\\xbd!\\x1d&<\\x1e\\x99[<\\xc4\\x97N\\xbd\\xef\\x0b\\xa4\\xbd\\xfc4\\a\\xbb\\x81\\x85.\\xbd\\x0f~\\xd3\\xbd\\xb6\\xf1^=!q\\x91=hR\\xa1<\\xf5K\\x91\\xbc\\xcf\\x0f<\\xbd\\x8eJ\\x8c\\xbd\\x9d\\x1d\\xb9=\\x8aDC=\\xef\\xb4\\x93<,k\\xc4\\xbc\\n\\x02A\\xbd\\xb7\\xea\\xb8\\xbd\\xe8\\xa2\\x91\\xbd\\a\\xae\\x05\\xbcGe\\xeb<\\x89;+\\xbdW\\x8a\\xd4\\xbd\\xe9P\\xb1=]\\x10\\x04\\xbb\\t \\xc4<\\x91\\xf8V\\xbc\\xe6s\\x81\\xbd\\xce\\xb7\\x90\\xbb3H\\xa6\\xbcDet\\xbczd\\x9f<\\x05Y\\xc4\\xbd.j[\\xbd\\xb3\\t\\x83< \\xb1\\xcd\\xbd\\xa8=o=\\x86\\xc6\\x0c\\xbb\\x1b\\xa1\\xa3=\\xc2F\\xd7<\\\"\\xc7\\\"<\\xa07\\x80<\\xd0$\\x86\\xbd\\xae\\x9f\\xde\\xbcdH\\x9d\\xbd\\xd4\\xf7\\xda<\\x9d\\xcb\\x82\\xbcU\\xd2\\xa5<\\x97$\\x94;<7\\x9b\\xbd\"\n",
            "5) \"full_text\"\n",
            "6) \"1900 PIPS Profit so far\\xf0\\x9f\\x94\\xa5\\xf0\\x9f\\x94\\xa5\\r\\n\\r\\nFor free signals, Join https://t.co/eRcU1NYwV1\\r\\n\\r\\n#bitcoin #Forex #amzn #fx $BTC #MT5 #MT4 #xagusd #GBPAUD #ForexAnalysis #nflx #ForexGroup #gbpjpy #forexsignals #stocks #METATRADER #usoil #forexnews 68016 https://t.co/WUP4laPFlT\"\n"
          ]
        }
      ],
      "source": [
        "#Check how the data is stored in Redis\n",
        "!redis-cli $REDIS_CONN hgetall \"tweet:1001\""
      ]
    },
    {
      "attachments": {},
      "cell_type": "markdown",
      "metadata": {
        "id": "ovtxchAGEG9t"
      },
      "source": [
        "## Query the database\n",
        "\n",
        "[Alway-on Streamlit app](https://antonum-redis-vss-streamlit-streamlit-app-p4z5th.streamlit.app/) \n",
        "\n",
        "\n",
        "Try queries like:\n",
        "“Oil”, “Oil Reserves”, “Fossil fuels”\n",
        "\n",
        "Lexical Full Text search quickly runs out of matches\n",
        "\n",
        "Vector search continues to discover relevant tweets"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "id": "koOnsz_NqUje"
      },
      "outputs": [],
      "source": [
        "user_query=\"oil price\"\n",
        "# queries to try \"oil reserve\", \"fossil fuels\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 44,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "629GJ972qnAP",
        "outputId": "c82fd0ea-5e9a-499a-80f3-7eb6cf09e18f"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-56b98a9b-ec6e-489a-aa2b-8fd7cd1dde15\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>id</th>\n",
              "      <th>full_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>tweet:3220</td>\n",
              "      <td>The relative performance of TIPS has historica...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>tweet:311</td>\n",
              "      <td>Oil Prices Rise, Fall As Russia, Saudi Arabia ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>tweet:1490</td>\n",
              "      <td>RT @Benzinga: Oil Prices Rise, Fall As Russia,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>tweet:1585</td>\n",
              "      <td>RT @Benzinga: Oil Prices Rise, Fall As Russia,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>tweet:1610</td>\n",
              "      <td>Oil Prices Rise, Fall As Russia, Saudi Arabia ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>tweet:7189</td>\n",
              "      <td>Do higher oil prices help the consumer and sma...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>tweet:636</td>\n",
              "      <td>Told you Saudi Arabia will bend the knee @jimc...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>tweet:5405</td>\n",
              "      <td>https://t.co/3IJBXa5wuf Historic oil price plu...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>tweet:5406</td>\n",
              "      <td>Historic oil price plunge trashes sector's pro...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>tweet:3865</td>\n",
              "      <td>Today's book recommendation goes for the winne...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-56b98a9b-ec6e-489a-aa2b-8fd7cd1dde15 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-56b98a9b-ec6e-489a-aa2b-8fd7cd1dde15');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "           id                                          full_text\n",
              "0  tweet:3220  The relative performance of TIPS has historica...\n",
              "1   tweet:311  Oil Prices Rise, Fall As Russia, Saudi Arabia ...\n",
              "2  tweet:1490  RT @Benzinga: Oil Prices Rise, Fall As Russia,...\n",
              "3  tweet:1585  RT @Benzinga: Oil Prices Rise, Fall As Russia,...\n",
              "4  tweet:1610  Oil Prices Rise, Fall As Russia, Saudi Arabia ...\n",
              "5  tweet:7189  Do higher oil prices help the consumer and sma...\n",
              "6   tweet:636  Told you Saudi Arabia will bend the knee @jimc...\n",
              "7  tweet:5405  https://t.co/3IJBXa5wuf Historic oil price plu...\n",
              "8  tweet:5406  Historic oil price plunge trashes sector's pro...\n",
              "9  tweet:3865  Today's book recommendation goes for the winne..."
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "#using Full Text Index\n",
        "q = Query(user_query)\\\n",
        "  .return_fields(\"full_text\")\n",
        "res = redis.ft(\"tweet:idx\").search(q)\n",
        "if res.total==0:\n",
        "  print(\"No matches found\")\n",
        "else:\n",
        "  res_df = pd.DataFrame([t.__dict__ for t in res.docs ]).drop(columns=[\"payload\"])\n",
        "  display(res_df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "PNZk10z9x4CD",
        "outputId": "9323bec8-33e6-45f8-a16e-7c12478370dc"
      },
      "outputs": [
        {
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>result_score</th>\n",
              "      <th>full_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>tweet:444</td>\n",
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              "      <td>Would you spend $2 more a gallon of gasoline i...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>tweet:11529</td>\n",
              "      <td>0.371095597744</td>\n",
              "      <td>RT @tradingcrudeoil: Crude oil closed up $0.48...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>tweet:5654</td>\n",
              "      <td>0.381934285164</td>\n",
              "      <td>..and oil still 25.74 LMAO  &amp;gt;&amp;gt;&amp;gt;NO DEM...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>tweet:204</td>\n",
              "      <td>0.396132171154</td>\n",
              "      <td>Bad news for #oil.  It’s going to between $10 ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>tweet:9189</td>\n",
              "      <td>0.409308671951</td>\n",
              "      <td>Oil erases gains for the day in fall to $25 ht...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>tweet:7189</td>\n",
              "      <td>0.429816782475</td>\n",
              "      <td>Do higher oil prices help the consumer and sma...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>tweet:9330</td>\n",
              "      <td>0.430081248283</td>\n",
              "      <td>The price of Texas intermediate oil (WTI) slum...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>tweet:531</td>\n",
              "      <td>0.431391596794</td>\n",
              "      <td>#OIL Sentiment ($22.50)\\r\\n\\r\\nWhat’s next for...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>tweet:178</td>\n",
              "      <td>0.441844820976</td>\n",
              "      <td>OH how bullish for #oil   LOL\\r\\n\\r\\n#OOTT #Oi...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>tweet:6867</td>\n",
              "      <td>0.442979931831</td>\n",
              "      <td>$DXY 99.55-0.57%&amp;lt;==US Dollar lower #Fed $2....</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
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              "            id    result_score  \\\n",
              "0    tweet:444  0.369450807571   \n",
              "1  tweet:11529  0.371095597744   \n",
              "2   tweet:5654  0.381934285164   \n",
              "3    tweet:204  0.396132171154   \n",
              "4   tweet:9189  0.409308671951   \n",
              "5   tweet:7189  0.429816782475   \n",
              "6   tweet:9330  0.430081248283   \n",
              "7    tweet:531  0.431391596794   \n",
              "8    tweet:178  0.441844820976   \n",
              "9   tweet:6867  0.442979931831   \n",
              "\n",
              "                                           full_text  \n",
              "0  Would you spend $2 more a gallon of gasoline i...  \n",
              "1  RT @tradingcrudeoil: Crude oil closed up $0.48...  \n",
              "2  ..and oil still 25.74 LMAO  &gt;&gt;&gt;NO DEM...  \n",
              "3  Bad news for #oil.  It’s going to between $10 ...  \n",
              "4  Oil erases gains for the day in fall to $25 ht...  \n",
              "5  Do higher oil prices help the consumer and sma...  \n",
              "6  The price of Texas intermediate oil (WTI) slum...  \n",
              "7  #OIL Sentiment ($22.50)\\r\\n\\r\\nWhat’s next for...  \n",
              "8  OH how bullish for #oil   LOL\\r\\n\\r\\n#OOTT #Oi...  \n",
              "9  $DXY 99.55-0.57%&lt;==US Dollar lower #Fed $2....  "
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "#using Vector Similarity Index\n",
        "query_vector=text_to_embedding(user_query)\n",
        "q = Query(\"*=>[KNN 10 @text_embedding $vector AS result_score]\")\\\n",
        "                .return_fields(\"result_score\",\"full_text\")\\\n",
        "                .dialect(2)\\\n",
        "                .sort_by(\"result_score\", True)\n",
        "res = redis.ft(\"tweet:idx\").search(q, query_params={\"vector\": query_vector})\n",
        "#print(res)\n",
        "res_df = pd.DataFrame([t.__dict__ for t in res.docs ]).drop(columns=[\"payload\"])\n",
        "res_df"
      ]
    }
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