From d2bb013b3a1218e3cd176b5e3e4e3611d457ac00 Mon Sep 17 00:00:00 2001 From: YanivHyper-Space <124336435+YanivHyper-Space@users.noreply.github.com> Date: Tue, 26 Mar 2024 08:36:47 +0200 Subject: [PATCH] Add files via upload --- .../BinaryVector/Binary_Vector_Search.ipynb | 1898 +++++++---------- 1 file changed, 821 insertions(+), 1077 deletions(-) diff --git a/DataSets/BinaryVector/Binary_Vector_Search.ipynb b/DataSets/BinaryVector/Binary_Vector_Search.ipynb index f48a661..a6fbe69 100644 --- a/DataSets/BinaryVector/Binary_Vector_Search.ipynb +++ b/DataSets/BinaryVector/Binary_Vector_Search.ipynb @@ -1,1098 +1,842 @@ { - "cells": [ - { - "cell_type": "markdown", - "source": [ - "![63f78014766fd30436c18a79_Hyperspace - navbar logo.png](data:image/png;base64,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)" - ], - "metadata": { - "id": "yZ7FEZEejbP9" - }, - "id": "yZ7FEZEejbP9" - }, - { - "cell_type": "markdown", - "source": [ - "# Binary Vector and Metadata Search with Hyperspace\n", - "This notebook demonstrates the use of Hyperspace engine for a hybrid search that combines vector search of binary vectors and metadata filtering over their corresponding metadata.\n", - "\n", - "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/hyper-space-io/QuickStart/blob/master/DataSets/BinaryVector/Binary_Vector_Search.ipynb)\n", - "# Hyperspace Hybrid search\n", - "This notenook combines approximate KNN (using IVF approximation) with metadata filtering. In this scheme, Hyperspace uses the post-filtering approach, by which the ANN matching is first perfomed, followed by metadata filtering.\n", - "\n", - 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- "\n", - "This approach optimizes the query recall, at the expanse of latency, as applying the filtering first may cause the data graph to become sparse and omit relevant results from the search.\n", - "![SparseGraph.PNG](data:image/png;base64,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)\n" - ], - "metadata": { - "id": "DQf1g53MLo9r" - }, - "id": "DQf1g53MLo9r" - }, - { - "cell_type": "markdown", - "source": [ - "# The Dataset\n", - "The dataset includes randomly generated binary vectors of dimension 800 and corresponding metadata, that describes stores for a recommednation engine.\n", - "\n", - "## The Dataset Fields\n", - "The metadata can be downloaded from [here](https://github.com/hyper-space-io/QuickStart/blob/main/DataSets/BinaryVector/Generated_data.hsv) includes the following fields:\n", - "1. **country** [string] - The Country in which the store is located\n", - "2. **city** [string] - The city in which the store is located\n", - "3. **street** [keyword] - The street in which the store is located\n", - "4. **zip_code** [integer] - The store zipcode\n", - "5. **open_now** [boolean] - Is the store open\n", - "6. **vertical** [keyword] - The store vertical (industry)\n", - "\n", - "# Setting up the Hyperspace Environment\n", - "Setting the environment and running the query includes the following steps\n", - "\n", - "1. Download and install the client API\n", - "2. Connect to a server\n", - "3. Create data schema file\n", - "4. Create collection\n", - "5. Ingest data\n", - "6. Define Logic and Run a Query" - ], - "metadata": { - "id": "-JeIE7JqVTu_" - }, - "id": "-JeIE7JqVTu_" - }, - { - "cell_type": "markdown", - "source": [ - "## 1. Install the Hyperspace client API\n", - "Hyperspace API can be installed directly from git, using the following command:" - ], - "metadata": { - "id": "qol984iQq_O4" - }, - "id": "qol984iQq_O4" - }, - { - "cell_type": "code", - "source": [ - "pip install git+https://github.com/hyper-space-io/hyperspace-py" - ], - "metadata": { - "id": "U6p1YrVOL19j", - "outputId": "d46b3aa4-dc98-4be9-9bfc-da829b083830", - "colab": { - "base_uri": "https://localhost:8080/" + "cells": [ + { + "cell_type": "markdown", + "source": [ + "![63f78014766fd30436c18a79_Hyperspace - navbar logo.png](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMoAAAAYCAYAAAC7k2KMAAAACXBIWXMAAAsTAAALEwEAmpwYAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAApoSURBVHgB7VtdaBzXFT737q6xXUimTfPiUHtNXdKmpZHBeTHUlqBN6Uts4R/8pvUfhL7oxwkE+uDVQyEQ25JeSsBKtHprYxvZfikNBq9TmpcEtKatgxu3HbXEeXBNNzI4RjtzT865Mzs7MzszO6NVYpHMB2Jn5v7/nHO+c+4VQI4cOXLkyJEjR46vCCLq4/FTF/cjKgMyYMOGUv3N14dNyJHja4guQTk2cem0AKxCZgiztEEOZRGW4xOX5jrF8cpbZw9eDuc58cqFQVRypP1uKzlZmw62QYI9DSiebL+/de7A0cj2SAFQvn3td1mwZ86/cbiRVFcYCHBzwwZ5OWmc4XaSYD8hx2vV4ab/28mxhQEl1WhcGSGhiYg3ouYrCi+/tlC2LDVKym8QURhCILUnqA4xT2OJVXCVsQWjINVUUj+U0vORSklyP1or6rT/W9T4kzBWXTCWl1WFxrAXEQZ0PwSYNJYrX+a6FP2JJCSV1QkJA3kSrleqCzvTDxwr7SeBuEQ/XQuvFJaFL1+xaM3TjxmoBUWD8nhCd2LiwtLsuUNVfx53kaa4n7o9gY2wkDh1wT7h5okCa5bWij114pVL07NnDoxH5kEcIIGqQApsbMIk/QTmC4uWAUpU4sqg0j9jpGhMamw8SWBY8VF/q27PHM2Iwn3DQZoTk/JMvn3uQC2iuOFfo6h+OPPBdVyYefvcoWlIgLWi9ofrKy5bN+knsVwbrDQfLNsLgvuFPi2PUHbHMkrCEDsf/ayLDFU02H5+6Zc/gpdefA5mzx6A3bu2dVX06q/3wOu/+RU8+/2nYfcL7XQsUwOZKNtaQC+ygHr7HUGMksAG+rGyokbAJwCWXRyGPoAKx0hYpuCxgsaDsHDy1XcGolLTKT6tiOa0tu2jHySCU7yRE3MBdFlJFOk0vHYHlLgOkLS/nPno1Y/VoBiXwEJy9d1bcPuf92ILc/rRI7vg/Q9MeNyQdmFcSXvRfTUKDzRl0BTMsSZtrQqsimbC9C0KbHUU4kznS8EQerEdgWNhIYGc7GFBmwhqPC7xkVHoaX0RkLQbml6/UA7SGDw6qixRpZ+ujU599dEcYQqpjlpWsVECKNtSDTjptMkFNCy7UIeeEDUE+0ZcP8iyc3v1qJIOhY6w1AiDL48tlN9MWA8fG/B1BWZofbTlQJusr78fSjK72A7JyLQusYJy9U8fkVV5Dq79+WO4//+HXel/+WBJCxNj8e+fwuPG+enhxvHxizM0YY7WQqzQ4szPnjlUdya5DWHatqymq1U0iU7U/F+ozoar2TRKy0wnoJZQCdVxOCm9J6SE+uyZw3Xfpxpp2G28yZxuiufDZdi/IKZd9uoAmDxPc+G+MuVsUJ56sWDPkZAMk+LoKbBUx43zwbHUaM7B26Tt/kQAkf3M9kYXJj2zZdDWwZJWhX6qcWWJDQz66TA9T86eDVDrOtFtk5iEqxjQYCsbRa19yLQuMjZFILzxu/dg4MfPwPeeCfq2mzeW4Bc/2wGNv92FP1y5Cd/99mZYD7CxUAUfr2QNx/SDnjxtS0s1mWZTxIE0sgnrAESTb/hee9JdJdRomKKxVZ09e3Con/kQQjRSZfQJEa8Blax33sVochvoSxdm2P9kWKo4LcniCYlDtips7yEkmZFIveBFIFq1BFu3GNoP4WcWkiP7n4dFEpJndzwNP9+zg6zPLf3eDxDkCGnJvd0JohwwuQngBSfBGPcce1ocevY2hxRw+fzZSKc1NaRUI4HuSWX2KGLQuK5HJZDTOQSrgEtFPA3NUZ9wHp4LarfubVAUA8oWi24AoEFK5EavKFEvcATqwXIgOhcpcE60qWMRlJJ1CsqYZJnbCsxgajbbsXhBuNEtDYqORmVxhT0y2hmDTOuSQL1ukaX4Fjz1Hcda/JCcdsbWLY51YSf+/v2HcO2Tj8mP+R/0D+2IlSO+QxawY08TMOLTYJ62bZEfAxnA4Uf/ZKITXSl3cpB2O3Ow3qMaI4mSpOuImKJ+uJsQDfK3yuAbl0IxE1XM9dtCDrAzzzSO/Ry9Y2EqlQpH0wgMkmbXc+uCIlADwbpFTPRN+IW67vqH5vEJPSZdngSXhaYeLkn0sExcoVMTdny1PpFpXWRiKnl7Dx+1nDgc/X3+0HnetKnk/G4uwXqEbRe6NAvz2jQOfAjOZLp/NORysFLMJHirhT4v8PohApuTN15MaFf7bURDdlI5DqlH0yuqkwRmka0UZOqH3mR+ITH5jCtcRteLHepLQj3va9v/PBKOVK4nxFMvcuQfft6Ca+/dgc2bivCfTz4jp/0u3P7XPR3pun3nnrYqO/f8QOdLio6lAk2aKGAt/JkOtGiDitOQASwQ5GTO+yMhzGFhjcCbk4RkMpYqBNEk3txXKDq2H4Dj5NQmjstVDhV+ZnpDtGegALBXgT4KaG9Mw1pJdqgT0OS1s1FWo3wdxxH39VnIJ49NvFPhZ/JN6ETHYwxGVGBEr+XERe+dwsllWBtkWpfEqBdv/iP7fkr+x6fw/odL+jsLxdzvP9TnKOyXXH33I4+e9QNy2MyojUeTWo65aZMJq3FYOTxMTXtWQ1jFJtlUM2NdzZQCldARGC7ZhUaLIlQBuiChp8PKGr1Nq9x+8N80U5qCE053qQ8M9KqL2p4hZebRK54PtlpJRbQj7mfPaE8Lj8gEabUSyIqt1l0J+HwtrfzGwlm039ay53rdNvAh07okRr1YGP5797Mua8HCwuHh3bvK2rr8485a+CjrEUJPZvuPN0U/EaJV90Jgk88ZwpTSPbeIBQU2pphWRR1IaksTEQRIgqQIV3g+kvI7tCuFALZBwhBFv8IRPr5tEM6jD5Sd4M0cjfnfa33omHzgSFaFQ8NPRYR/d/5kiz5w5Hy7X9iqLUuOSBgU46/GJVpPFKfTXvnhzU11TXrnBbQxjk1cGIu6OuLe2dOaV9ly8fipSzUh1HyRwtt2qWWQ0NHG6kQEUcjLsMZotVTwwBPUfFQ+9FHr4rLFfa7605k2F2TnZgXfNqDx0HM7Akan++i/GpMuyJJlXRKpF1sVFojFv0aHfllImIatBfX6GsPABB9rY1NTjdRWqnvTiNOkubvCvJKJjJ+y0kYiC1RpSYog2RJEgPYIMy4g0BeCUaV61PkHQx8LuHnJB+k6ImArfnJsYTgQwXMEo9JuyIcmBRXShN0zrUuAeqHv8IitBQvLiVOXPP/EDz6MfO23f9S0jM9XHAjzkQFfOTX5JoE3DV9F8X0ymJuH8/GmpI1w1DkFjwcHJlJurExwqI/vNF1GWxOdhqJzNkICE0WbvAhe4ng48lYYWkV0sycCFoW0yjSZo0RJi4cODw5luTIt9B0mFzL6jlBBlRooLS9f6pNxCZdXE3MnXUtnEs7/4iiUJqwGNBah0p3/RCmWYrFoUhQqdszsH5ygg9V2P1mhMrcPz71rJWr6npUt9gsJ+qoLbcymQlxix7yHQ9sMrFFBZTrt9pdNasdSslaUVs/QsCsA2/VlT8RBGs823Q7S3gO4SRG9WqIP2ce6rNk/bilVqn8ZkpwjR44cOXLkyJEjR45vFL4Aeoh6Zli/bmMAAAAASUVORK5CYII=)" + ], + "metadata": { + "id": "yZ7FEZEejbP9" + }, + "id": "yZ7FEZEejbP9" }, - "ExecuteTime": { - "end_time": "2024-01-01T19:34:20.670682300Z", - "start_time": "2024-01-01T19:34:13.179071800Z" - } - }, - "id": "U6p1YrVOL19j", - "execution_count": 3, - "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting git+https://github.com/hyper-space-io/hyperspace-py\n", - " Cloning https://github.com/hyper-space-io/hyperspace-py to c:\\users\\tamirbracha\\appdata\\local\\temp\\pip-req-build-5xyh181q\n", - " Resolved https://github.com/hyper-space-io/hyperspace-py to commit c49c83710c5b466a4bb299f7ad70f618d3a6df94\n", - " Preparing metadata (setup.py): started\n", - " Preparing metadata (setup.py): finished with status 'done'\n", - "Requirement already satisfied: certifi>=14.05.14 in c:\\users\\tamirbracha\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from hyperspace==1.0.0) (2023.7.22)\n", - "Requirement already satisfied: six>=1.10 in c:\\users\\tamirbracha\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from hyperspace==1.0.0) (1.12.0)\n", - "Requirement already satisfied: python_dateutil>=2.5.3 in c:\\users\\tamirbracha\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from hyperspace==1.0.0) (2.8.2)\n", - "Requirement already satisfied: setuptools>=21.0.0 in c:\\users\\tamirbracha\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from hyperspace==1.0.0) (68.0.0)\n", - "Requirement already satisfied: urllib3>=1.15.1 in c:\\users\\tamirbracha\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from hyperspace==1.0.0) (2.0.3)\n", - "Requirement already satisfied: msgpack in c:\\users\\tamirbracha\\appdata\\local\\programs\\python\\python310\\lib\\site-packages (from hyperspace==1.0.0) (1.0.7)\n", - "Note: you may need to restart the kernel to use updated packages.\n" - ] + "cell_type": "markdown", + "source": [ + "# Binary Vector and Metadata Search with Hyperspace\n", + "This notebook demonstrates the use of Hyperspace engine for a hybrid search that combines vector search of binary vectors and metadata filtering over their corresponding metadata.\n", + "\n", + "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/hyper-space-io/QuickStart/blob/master/DataSets/BinaryVector/Binary_Vector_Search.ipynb)\n", + "# Hyperspace Hybrid search\n", + "This notenook combines approximate KNN (using IVF approximation) with metadata filtering. In this scheme, Hyperspace uses the post-filtering approach, by which the ANN matching is first perfomed, followed by metadata filtering.\n", + "\n", + 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+ "\n", + "This approach optimizes the query recall, at the expanse of latency, as applying the filtering first may cause the data graph to become sparse and omit relevant results from the search.\n", + "![SparseGraph.PNG](data:image/png;base64,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)\n" + ], + "metadata": { + "id": "DQf1g53MLo9r" + }, + "id": "DQf1g53MLo9r" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - " Running command git clone --filter=blob:none --quiet https://github.com/hyper-space-io/hyperspace-py 'C:\\Users\\TamirBracha\\AppData\\Local\\Temp\\pip-req-build-5xyh181q'\n", - "DEPRECATION: textract 1.6.5 has a non-standard dependency specifier extract-msg<=0.29.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of textract or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\n", - "WARNING: There was an error checking the latest version of pip.\n" - ] - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "## 2. Connect to a server\n", - "\n", - "Once the Hyperspace API is installed, the database can be accessed by creating a local instance of the Hyperspace client. This step requires host address, username and password." - ], - "metadata": { - "id": "EtEeKuxJ7E2Q" - }, - "id": "EtEeKuxJ7E2Q" - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "4161f9f8", - "metadata": { - "id": "4161f9f8", - "ExecuteTime": { - "end_time": "2024-01-01T19:34:21.863030600Z", - "start_time": "2024-01-01T19:34:20.675693200Z" - } - }, - "outputs": [], - "source": [ - "import hyperspace\n", - "from getpass import getpass\n", - "\n", - "username = \"USERNAME\"\n", - "host = \"HOST_URL\"\n", - "\n", - "hyperspace_client = hyperspace.HyperspaceClientApi(host=host, username=username, password=getpass())" - ] - }, - { - "cell_type": "markdown", - "source": [ - "Before continuing, let us check that the cluster is live" - ], - "metadata": { - "id": "yQb-y862X7Ec" - }, - "id": "yQb-y862X7Ec" - }, - { - "cell_type": "code", - "source": [ - "collections_info = hyperspace_client.collections_info()\n", - "display(collections_info)" - ], - "metadata": { - "id": "pl7oBXaTYDMq", - "outputId": "daa8cca8-ed8e-4b0b-b54e-354c7fd77900", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 199 + "cell_type": "markdown", + "source": [ + "# The Dataset\n", + "The dataset includes randomly generated binary vectors of dimension 800 and corresponding metadata, that describes stores for a recommednation engine.\n", + "\n", + "## The Dataset Fields\n", + "The metadata can be downloaded from [here](https://github.com/hyper-space-io/QuickStart/blob/main/DataSets/BinaryVector/Generated_data.hsv) includes the following fields:\n", + "1. **country** [string] - The Country in which the store is located\n", + "2. **city** [string] - The city in which the store is located\n", + "3. **street** [keyword] - The street in which the store is located\n", + "4. **zip_code** [integer] - The store zipcode\n", + "5. **open_now** [boolean] - Is the store open\n", + "6. **vertical** [keyword] - The store vertical (industry)\n", + "\n", + "# Setting up the Hyperspace Environment\n", + "Setting the environment and running the query includes the following steps\n", + "\n", + "1. Download and install the client API\n", + "2. Connect to a server\n", + "3. Create data schema file\n", + "4. Create collection\n", + "5. Ingest data\n", + "6. Define Logic and Run a Query" + ], + "metadata": { + "id": "-JeIE7JqVTu_" + }, + "id": "-JeIE7JqVTu_" }, - "ExecuteTime": { - "end_time": "2024-01-01T19:34:22.117269100Z", - "start_time": "2024-01-01T19:34:21.866029900Z" - } - }, - "id": "pl7oBXaTYDMq", - "execution_count": 5, - "outputs": [ { - "data": { - "text/plain": "{'collections': {'all-MiniLM-L6-v2_arXiv': {'creation_time': '2024-01-01T19:23:25Z',\n 'last_query_time': '2024-01-01T19:25:41Z',\n 'size': 100001}}}" - }, - "metadata": {}, - "output_type": "display_data" - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "## 3. Create a Data Schema File\n", - "\n", - "Similarly to other search databases, Hyper-Space database requires a configuration file that outlines the data schema. Here, we create a config file that corresponds to the fields of the given dataset.\n", - "\n", - "For vector fields, we also provide the index type to be used, and the metric. . Current options for index include \"**brute_force**\", \"**hnsw**\", \"**ivf**\", and \"**bin_ivf**\" for binary vectors, and \"**IP**\" (inner product) as a metric for floating point vectors and \"**Hamming**\" ([hamming distance](https://en.wikipedia.org/wiki/Hamming_distance)) for binary vectors.\n", - "Note that the key 'low_cardinality' enables faster search for low cardinality fields." - ], - "metadata": { - "id": "6BG-FyOlujHE" - }, - "id": "6BG-FyOlujHE" - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "976b2177", - "metadata": { - "id": "976b2177", - "ExecuteTime": { - "end_time": "2024-01-01T19:34:22.189609900Z", - "start_time": "2024-01-01T19:34:22.122809Z" - } - }, - "outputs": [], - "source": [ - "import json\n", - "vector_dimension = 800 # bits\n", - "config = {\n", - " \"configuration\": {\n", - " \"id\": {\n", - " \"type\": \"keyword\",\n", - " \"id\": True\n", - " },\n", - " 'city': {\"type\": 'keyword'},\n", - " 'country': {\"type\": 'keyword'},\n", - " 'open_now': {\"type\": 'boolean'},\n", - " 'zip_code': {\"type\": 'integer'},\n", - " 'street': {\"type\": 'keyword'},\n", - " 'vertical': {\"type\": 'keyword', 'low_cardinality': True},\n", - " \"vector\": {\n", - " \"type\": \"dense_vector\",\n", - " \"index_type\": \"bin_ivf\",\n", - " \"dim\": vector_dimension,\n", - " \"metric\": \"hamming\"\n", - " }\n", - " }\n", - "}\n", - "\n", - "with open('config.json', 'w') as f:\n", - " f.write(json.dumps(config, indent=2))\n" - ] - }, - { - "cell_type": "markdown", - "source": [ - "## 4. Create Collection\n", - "The Hyerspace engine stroes data in Collections, where each collecction commonly hosts data of similar context, etc. Each search is then perfomed within a collection. We create a collection using the command \"**create_collection**(schema_filename, collection_name)\"." - ], - "metadata": { - "id": "g1DHlx75uklY" - }, - "id": "g1DHlx75uklY" - }, - { - "cell_type": "code", - "source": [ - "collection_name = 'GeneratedData'\n", - "\n", - "if collection_name not in hyperspace_client.collections_info()[\"collections\"]:\n", - " hyperspace_client.create_collection('config.json', collection_name)\n", - "\n", - "hyperspace_client.collections_info()" - ], - "metadata": { - "id": "z43Vz3nabLZe", - "outputId": "75803675-218a-41a3-fa3e-89c3f67ad3a2", - "colab": { - "base_uri": "https://localhost:8080/" + "cell_type": "markdown", + "source": [ + "## 1. Install the Hyperspace client API\n", + "Hyperspace API can be installed directly from git, using the following command:" + ], + "metadata": { + "id": "qol984iQq_O4" + }, + "id": "qol984iQq_O4" }, - "ExecuteTime": { - "end_time": "2024-01-01T19:34:22.583664500Z", - "start_time": "2024-01-01T19:34:22.149799700Z" - } - }, - "id": "z43Vz3nabLZe", - "execution_count": 7, - "outputs": [ { - "data": { - "text/plain": "{'collections': {'GeneratedData': {'creation_time': '2024-01-01T19:34:22Z',\n 'size': 0},\n 'all-MiniLM-L6-v2_arXiv': {'creation_time': '2024-01-01T19:23:25Z',\n 'last_query_time': '2024-01-01T19:25:41Z',\n 'size': 100001}}}" - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "# 5. Ingest data\n", - "\n", - "In the next step we ingest the dataset in batches of 250 documents. This number can be controlled by user, and in particular, can be increased in order improve ingestion time. We add batches of data using the command **add_batch**(batch, collection_name)." - ], - "metadata": { - "id": "9eUT0cBRu31m" - }, - "id": "9eUT0cBRu31m" - }, - { - "cell_type": "code", - "source": [ - "import random\n", - "import secrets\n", - "import base64\n", - "\n", - "def generate_data(metadata, vector_dimension):\n", - " data_point = random.choice(metadata)\n", - " random_bytes = secrets.token_bytes(vector_dimension // 8)\n", - " data_point['vector'] = base64.b64encode(random_bytes).decode()\n", - " return data_point" - ], - "metadata": { - "id": "_XCNBaIHLjZZ", - "ExecuteTime": { - "end_time": "2024-01-01T19:34:22.597661700Z", - "start_time": "2024-01-01T19:34:22.585667600Z" - } - }, - "id": "_XCNBaIHLjZZ", - "execution_count": 8, - "outputs": [] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "95086784", - "metadata": { - "id": "95086784", - "ExecuteTime": { - "end_time": "2024-01-01T19:35:07.446200300Z", - "start_time": "2024-01-01T19:34:22.603667200Z" - } - }, - "outputs": [ + "cell_type": "code", + "source": [ + "pip install git+https://github.com/hyper-space-io/hyperspace-py" + ], + "metadata": { + "id": "U6p1YrVOL19j", + "outputId": "16986439-fb1d-4884-927d-4fa40228ccf9", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "ExecuteTime": { + "end_time": "2024-01-01T19:34:20.670682300Z", + "start_time": "2024-01-01T19:34:13.179071800Z" + } + }, + "id": "U6p1YrVOL19j", + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting git+https://github.com/hyper-space-io/hyperspace-py\n", + " Cloning https://github.com/hyper-space-io/hyperspace-py to /tmp/pip-req-build-_8mrdqbv\n", + " Running command git clone --filter=blob:none --quiet https://github.com/hyper-space-io/hyperspace-py /tmp/pip-req-build-_8mrdqbv\n", + " Resolved https://github.com/hyper-space-io/hyperspace-py to commit 70d23409dc1b8be4a73845f17f6b8f84a104b4ea\n", + " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + "Requirement already satisfied: certifi>=14.05.14 in /usr/local/lib/python3.10/dist-packages (from hyperspace==1.0.0) (2024.2.2)\n", + "Requirement already satisfied: six>=1.10 in /usr/local/lib/python3.10/dist-packages (from hyperspace==1.0.0) (1.16.0)\n", + "Requirement already satisfied: python_dateutil>=2.5.3 in /usr/local/lib/python3.10/dist-packages (from hyperspace==1.0.0) (2.8.2)\n", + "Requirement already satisfied: setuptools>=21.0.0 in /usr/local/lib/python3.10/dist-packages (from hyperspace==1.0.0) (67.7.2)\n", + "Requirement already satisfied: urllib3>=1.15.1 in /usr/local/lib/python3.10/dist-packages (from hyperspace==1.0.0) (2.0.7)\n", + "Requirement already satisfied: msgpack in /usr/local/lib/python3.10/dist-packages (from hyperspace==1.0.0) (1.0.8)\n", + "Building wheels for collected packages: hyperspace\n", + " Building wheel for hyperspace (setup.py) ... \u001b[?25l\u001b[?25hdone\n", + " Created wheel for hyperspace: filename=hyperspace-1.0.0-py3-none-any.whl size=38874 sha256=3afc7add90e2b5b300414e43ff89ba6d65e03f1e9626725dda95efd1de900225\n", + " Stored in directory: /tmp/pip-ephem-wheel-cache-e67f250h/wheels/c4/96/59/f4b91d653fdbfc819e48a7dacbea1c9f3de59a1bc113aa840d\n", + "Successfully built hyperspace\n", + "Installing collected packages: hyperspace\n", + "Successfully installed hyperspace-1.0.0\n" + ] + } + ] + }, { - 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"74750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "75000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "75250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "75500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "75750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "76000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "76250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "76500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "76750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "77000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "77250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "77500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "77750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - 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"81250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "81500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "81750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "82000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "82250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "82500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "82750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "83000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "83250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "83500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "83750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "84000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "84250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "84500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "84750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "85000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "85250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "85500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "85750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "86000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "86250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "86500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "86750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "87000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "87250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "87500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - 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"91000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "91250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "91500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "91750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "92000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "92250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "92500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "92750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "93000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "93250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "93500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "93750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "94000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "94250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "94500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "94750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "95000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "95250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "95500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "95750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "96000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "96250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "96500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "96750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "97000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "97250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "97500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "97750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "98000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "98250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "98500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "98750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "99000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "99250 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "99500 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "99750 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n", - "100000 {'code': 200, 'message': 'Batch successfully added', 'status': 'OK'}\n" - ] + "cell_type": "markdown", + "source": [ + "## 2. Connect to a server\n", + "\n", + "Once the Hyperspace API is installed, the database can be accessed by creating a local instance of the Hyperspace client. This step requires host address, username and password." + ], + "metadata": { + "id": "EtEeKuxJ7E2Q" + }, + "id": "EtEeKuxJ7E2Q" }, { - "data": { - "text/plain": "{'code': 200, 'message': 'Dataset committed successfully', 'status': 'OK'}" - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pickle\n", - "\n", - "data_path = 'Generated_data.hsv'\n", - "with open(data_path, 'rb') as file:\n", - " metadata = pickle.load(file)\n", - "\n", - "BATCH_SIZE = 250\n", - "\n", - "batch = []\n", - "data = []\n", - "\n", - "\n", - "for i, vec in enumerate(range(100000)):\n", - " data_point = generate_data(metadata, vector_dimension)\n", - " data_point[\"id\"] = str(i)\n", - " batch.append(dict(data_point))\n", - "\n", - " if (i+1) % BATCH_SIZE == 0:\n", - " response = hyperspace_client.add_batch(batch, collection_name)\n", - " print(i + 1, response)\n", - " batch.clear()\n", - "\n", - "if batch:\n", - " hyperspace_client.add_batch(batch, collection_name)\n", - " response = hyperspace_client.add_batch(batch, collection_name)\n", - "\n", - "hyperspace_client.commit(collection_name)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "source": [ - "#6. Define Logic and Run a Query\n", - "We will build a hybrid search query using Hyper-space. In the query, we will select a document and find similar ones. We must first compile the score function using the \"set_function\" command." - ], - "metadata": { - "id": "Yjo-yZwXDjkS" - }, - "id": "Yjo-yZwXDjkS" - }, - { - "cell_type": "code", - "source": [ - "import inspect\n", - "\n", - "def set_score_function(func, collection_name, score_function_name='func'):\n", - " source = inspect.getsource(func)\n", - " with open('sf.py', 'w') as f:\n", - " f.write(source)\n", - " hyperspace_client.set_function('sf.py', collection_name, score_function_name)\n" - ], - "metadata": { - "id": "Q-DQqoBpeETW", - "ExecuteTime": { - "end_time": "2024-01-01T19:35:07.490319600Z", - "start_time": "2024-01-01T19:35:07.450154700Z" - } - }, - "id": "Q-DQqoBpeETW", - "execution_count": 10, - "outputs": [] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "5c6e2ccb", - "metadata": { - "id": "5c6e2ccb", - "ExecuteTime": { - "end_time": "2024-01-01T19:35:08.570400500Z", - "start_time": "2024-01-01T19:35:07.465928200Z" - } - }, - "outputs": [], - "source": [ - "def similarity_score(params, doc):\n", - " score = 0.0\n", - " if match(\"country\"):\n", - " score = 5.0\n", - " if match(\"street\"):\n", - " score = 10.0\n", - " return score\n", - "\n", - "set_score_function(similarity_score, collection_name, score_function_name='similarity_score')" - ] - }, - { - "cell_type": "markdown", - "source": [ - "The next step is to retrieve a document and perform simialrity search." - ], - "metadata": { - "id": "RnQ4hgtueZ2j" - }, - "id": "RnQ4hgtueZ2j" - }, - { - "cell_type": "code", - "source": [ - "input_document = hyperspace_client.get_document(collection_name, 65)\n", - "input_document" - ], - "metadata": { - "id": "JpPhJG0wMsNg", - "outputId": "0b20a2d0-f55a-413e-8519-db377d5646c4", - "colab": { - "base_uri": "https://localhost:8080/" + "cell_type": "code", + "execution_count": 3, + "id": "4161f9f8", + "metadata": { + "id": "4161f9f8", + "ExecuteTime": { + "end_time": "2024-01-01T19:34:21.863030600Z", + "start_time": "2024-01-01T19:34:20.675693200Z" + } + }, + "outputs": [], + "source": [ + "import hyperspace\n", + "from getpass import getpass\n", + "\n", + "username = \"USERNAME\"\n", + "host = \"HOST_URL\"\n", + "\n", + "hyperspace_client = hyperspace.HyperspaceClientApi(host=host, username=username, password=getpass())" + ] }, - "ExecuteTime": { - "end_time": "2024-01-01T19:35:08.664430400Z", - "start_time": "2024-01-01T19:35:08.574444200Z" - } - }, - "id": "JpPhJG0wMsNg", - "execution_count": 12, - "outputs": [ { - "data": { - "text/plain": "{'city': 'North Andrew',\n 'country': 'Croatia',\n 'open_now': False,\n 'zip_code': 92543,\n 'vector': 'X5gYG7oS8VMDBzhYHRhtqIEylHrh/II+tXpBVtZFPotal7gRAq2++M1Bf5MgtxD3ebghfg1SD9H8IMWrVhJXnBr/kGx3pINOOjewX6Ei+yUB40fUx9QSA6aSMmHGt63svrzY0Q==',\n 'id': '65'}" - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ] - }, - { - "cell_type": "markdown", - "source": [ - "# Vector Search" - ], - "metadata": { - "id": "URXMq9eUHxKh" - }, - "id": "URXMq9eUHxKh" - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "5ff98e9d", - "metadata": { - "id": "5ff98e9d", - "outputId": "100117d8-839b-46d4-dee8-7fee5c413c39", - "colab": { - "base_uri": "https://localhost:8080/" + "cell_type": "markdown", + "source": [ + "Before continuing, let us check that the cluster is live" + ], + "metadata": { + "id": "yQb-y862X7Ec" + }, + "id": "yQb-y862X7Ec" }, - "ExecuteTime": { - "end_time": "2024-01-01T19:35:08.757574300Z", - "start_time": "2024-01-01T19:35:08.664430400Z" - } - }, - "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Query run time: 2.00ms\n", - "[{'document_id': '17462', 'score': 356.0},\n", - " {'document_id': '99138', 'score': 356.0},\n", - " {'document_id': '35344', 'score': 355.0},\n", - " {'document_id': '74306', 'score': 355.0},\n", - " {'document_id': '96339', 'score': 355.0},\n", - " {'document_id': '99973', 'score': 355.0},\n", - " {'document_id': '43130', 'score': 354.0},\n", - " {'document_id': '97431', 'score': 354.0},\n", - " {'document_id': '44183', 'score': 353.0},\n", - " {'document_id': '17057', 'score': 351.0},\n", - " {'document_id': '37998', 'score': 349.0},\n", - " {'document_id': '88328', 'score': 349.0},\n", - " {'document_id': '68018', 'score': 347.0},\n", - " {'document_id': '76859', 'score': 346.0},\n", - " {'document_id': '65', 'score': 0.0}]\n" - ] - } - ], - "source": [ - "import random\n", - "from pprint import pprint\n", - "\n", - "\n", - "query_with_knn = {\n", - " 'params': input_document,\n", - " \"query\": {\"boost\": 0},\n", - " 'vector':{\"boost\": 10}\n", - "}\n", - "\n", - "results = hyperspace_client.search(query_with_knn,\n", - " size=15,\n", - " collection_name=collection_name)\n", - "candidates = results['candidates']\n", - "\n", - "print(f\"Query run time: {results['took_ms']:.2f}ms\")\n", - "pprint(results['similarity'])\n" - ] - }, - { - "cell_type": "markdown", - "source": [ - "# Results\n", - "The results are sorted by Hamming distance, as expected." - ], - "metadata": { - "id": "5lzGiQ3ON9bW" - }, - "id": "5lzGiQ3ON9bW" - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "ddd7d6a1", - "metadata": { - "id": "ddd7d6a1", - "outputId": "ad5c3ea4-aa01-4c6a-8208-6b66d5c3e5ea", - "colab": { - "base_uri": "https://localhost:8080/" + "cell_type": "code", + "source": [ + "collections_info = hyperspace_client.collections_info()\n", + "display(collections_info)" + ], + "metadata": { + "id": "pl7oBXaTYDMq", + "outputId": "2476a6ca-3369-4fcf-a031-633f06c06774", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 121 + }, + "ExecuteTime": { + "end_time": "2024-01-01T19:34:22.117269100Z", + "start_time": "2024-01-01T19:34:21.866029900Z" + } + }, + "id": "pl7oBXaTYDMq", + "execution_count": 4, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "{'collections': {'DocRetrievalEmbedded': {'creation_time': '2024-03-20T10:50:16Z',\n", + " 'last_query_time': '2024-03-25T09:27:27Z',\n", + " 'size': 39},\n", + " 'GeneratedData': {'creation_time': '2024-03-26T05:27:09Z',\n", + " 'last_query_time': '2024-03-26T06:24:53Z',\n", + " 'size': 100000}}}" + ] + }, + "metadata": {} + } + ] }, - "ExecuteTime": { - "end_time": "2024-01-01T19:35:09.886289900Z", - "start_time": "2024-01-01T19:35:08.762573600Z" - } - }, - "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "0 {'city': 'South Steven', 'country': 'Honduras', 'open_now': True, 'zip_code': 58113, 'vertical': 'jungle', 'vector': 'XV1vmYSScRUYB5qk/i3y4TBwLiD1vZUcpxv6ZFluLKVXL3hrqWruMf7C3jn16Havay2JHFOLbCWscma0Y32jeIMWKWRjRxsMDjsQL2sig9QFhmD6kh+oEqWy8NbUNCF1eUq2lw==', 'id': '17462'}\n", - "1 {'city': 'Robertview', 'country': 'Zambia', 'open_now': False, 'zip_code': 81403, 'vector': 'zJgBmeiToUsRCigTjQsFO9ixMjcg0QXYp9IX+bJJjQHnTjRSTEYXgDR9z6PUlDeTT6eRdihEGo0im3TLAiKI6YqrGLPysb1KQR+poSiKOmwxwiiKW/XQnGSH9BWPM88pj0ZmXA==', 'id': '99138'}\n", - "2 {'city': 'East Tracy', 'country': 'Belgium', 'open_now': False, 'zip_code': 64267, 'vertical': 'noodle', 'vector': 'W0HW2kU6OMmKl7RxZTjmqaN1Fq4l1u3l1J4sZqoovp2JDLrZSnrK/b8hO3BX5iOBE6ANYpowNAIkcfOtW5SPRw6TB3LjqQI+fBJT85hTkycl4PNH0BrK7trqUgLKqJRiopocuQ==', 'id': '35344'}\n", - "3 {'city': 'New Emilystad', 'country': 'Jersey', 'open_now': False, 'zip_code': 10183, 'street': 'zebra', 'vector': 'zSgcO42N0RcabLDbH36NesI1SSqYpOWGaiEbB/UhiUR6nm1On/g4OqrZL66hB25yWtT9ag5GCpHNTbiGuT4tjA9PjVqtlvAio/4umTw2lYUNpdSgC5UJUXOaIAbt/XjWvvbsGw==', 'id': '74306'}\n", - "4 {'city': 'Lake Johnstad', 'country': 'Ecuador', 'open_now': False, 'zip_code': 98539, 'street': 'ocean', 'vector': 'rpGVVsc6iZ1AN0dtIyiOiQVIyXAnXRoylaqRddykxkXcjbWc9ZQ3KTfW4AMc9luUcRuo+qh7N6h4IUrhySIIDVtb489Klkm0sn2kGkrT8/Vn4KZSs1bMi7JmcgrdvC/ICb8T6Q==', 'id': '96339'}\n", - "5 {'city': 'Bradleyton', 'country': 'Cape Verde', 'open_now': False, 'zip_code': 53080, 'street': 'xylophone', 'vector': 'SXRJsDJoM3NaJivcv8qvCtmxQCxAg4gA8+MBYA7TPxEo9IGyqvmKey8CTE2ThWrice1Lhnnebs7PbnTM7sl0yToSoLHUlEHctmy/viWzr6T7xlsXsqGm05MXsCEohhtYoKzLkA==', 'id': '99973'}\n", - "6 {'city': 'Jenniferberg', 'country': 'Congo', 'open_now': False, 'zip_code': 30878, 'vector': 'uHtIlBNl+GMbAyUexBLqX/bYWemiREVUI/55RTY/JBlWwbc0Sy4eWK7aZp/8sxrSedwzuNeQN1ckJ9+u6QJuCc93LVjWEpS9ghjUy6BDjkzvd025XYLWAP7BB2x5qqdN53QYdQ==', 'id': '43130'}\n", - "7 {'city': 'New Sheila', 'country': 'Belarus', 'open_now': False, 'zip_code': 16013, 'street': 'ice cream', 'vector': '75Tq/ZwCaH3VK3vVDln37khiZnCXuo/LOLlXJUB7Khu/cJDgDkf06Gy9eyPUCRlfYjQCD8XWF1LzDBwqqhHmqh0xWPFFjSVYvjrmClia3n8189oaOtwxQDPT8/AGMSeDvoFsPg==', 'id': '97431'}\n", - "8 {'city': 'Valdezborough', 'country': 'Serbia', 'open_now': True, 'zip_code': 44900, 'street': 'sun', 'vector': 'rq4LMe8ZDX2fx9F4uzC8uEMm8mtz/XBF96jBoZcjRnYWJ4pWa/OKk9RJAEEDlv49FQFRW4xzEaJ596m73tP+moOkxNDtlC8uPJoyMSgF4G6Hx0m5hXNZTTIxun1A9nodjWbNww==', 'id': '44183'}\n", - "9 {'city': 'Lake Michaelberg', 'country': 'Ghana', 'open_now': False, 'zip_code': 15316, 'street': 'rainbow', 'vector': 'kpE3ihzWu04xHfjQ1aY34M1kZDXpxZ98N3KUNKXYlhN+QUhSDCsu5c8RtipY10b1vhb1z2DCFWjPYIOfnXrlpeV0miUxAZ7UPmqkX76t1bshMOfM0znFGLAJQONTQ7Z3jZKG8w==', 'id': '17057'}\n", - "10 {'city': 'West Markmouth', 'country': 'Sierra Leone', 'open_now': False, 'zip_code': 76021, 'vector': 'n8MiB7Itk3QPubsEAJ3kzr/6Th9j1w5GEGvWUsBQRIPlT9AGiovS2A+j19ciY9BzFuvj+/scTRtMPRLDpwUZuR/Fs7I7vsN12uXIQqGkaOXBunCRP4i6j2xwsHv4Ub4gvwJz4w==', 'id': '37998'}\n", - "11 {'city': 'Jonesville', 'country': 'Niger', 'open_now': True, 'zip_code': 25186, 'vertical': 'xylophone', 'street': 'sun', 'vector': '0gpQE/7HXBMrXzHGTSW8GgCwamuyboh5YfNldgQInRmUHt5ESj3ceA+rjxIkdXEn9YdyfG/AX+WO7CMbXufQH4fhzgLaIXHkGnvQbkXakXRyPlzP+NXGeM8j4cGlV4qHrRl2Rg==', 'id': '88328'}\n", - "12 {'city': 'East Rachel', 'country': 'Grenada', 'open_now': True, 'zip_code': 63920, 'vector': '93DenhewDQUyOjZo/SIimZDxpPhpvSkY9vRQtkDfeZ56GfBkm8meMrWPyPjg+CnX7jyYNANW+pozZXYhV9ZUA0j3XURYFkIETkHNNaAm9QxTp3eOr2bDa4kcIqDMbpJwo3PN/Q==', 'id': '68018'}\n", - "13 {'city': 'Lake Ericton', 'country': 'Bangladesh', 'open_now': True, 'zip_code': 82176, 'vertical': 'sun', 'street': 'noodle', 'vector': 'n5KTYYcSII+fJ+fXfIqZo+oVWCvhY4B/r2oP1eIRXpSqNmlYQz8j6eQtNgAO0REDd9Zv9LtOLtAT0WQQ8BO2fthprvx+ZuFg9ZJSXwh2peAGQylkb9WfN4nSTjqSDwOEpi8iWQ==', 'id': '76859'}\n", - "14 {'city': 'North Andrew', 'country': 'Croatia', 'open_now': False, 'zip_code': 92543, 'vector': 'X5gYG7oS8VMDBzhYHRhtqIEylHrh/II+tXpBVtZFPotal7gRAq2++M1Bf5MgtxD3ebghfg1SD9H8IMWrVhJXnBr/kGx3pINOOjewX6Ei+yUB40fUx9QSA6aSMmHGt63svrzY0Q==', 'id': '65'}\n" - ] - } - ], - "source": [ - "for i, x in enumerate(results['similarity']):\n", - " document = hyperspace_client.get_document(collection_name, x[\"document_id\"])\n", - " print(i, document)" - ] - }, - { - "cell_type": "markdown", - "source": [ - "#Hybrid Search" - ], - "metadata": { - "id": "sd6AQ5Y3IEaH" - }, - "id": "sd6AQ5Y3IEaH" - }, - { - "cell_type": "code", - "source": [ - "import random\n", - "from pprint import pprint\n", - "\n", - "\n", - "query_with_knn = {\n", - " 'params': input_document,\n", - " \"query\": {\"boost\": 0},\n", - " 'vector':{\"boost\": 10}\n", - "}\n", - "\n", - "results = hyperspace_client.search(query_with_knn,\n", - " size=15,\n", - " function_name='similarity_score',\n", - " collection_name=collection_name)\n", - "candidates = results['candidates']\n", - "\n", - "print(f\"Query run time: {results['took_ms']:.2f}ms\")\n", - "pprint(results['similarity'])\n" - ], - "metadata": { - "id": "m6pMqw6NIH_K", - "ExecuteTime": { - "end_time": "2024-01-01T19:35:09.979062300Z", - "start_time": "2024-01-01T19:35:09.889289800Z" - } - }, - "id": "m6pMqw6NIH_K", - "execution_count": 15, - "outputs": [ + "cell_type": "markdown", + "source": [ + "## 3. Create a Data Schema File\n", + "\n", + "Similarly to other search databases, Hyper-Space database requires a configuration file that outlines the data schema. Here, we create a config file that corresponds to the fields of the given dataset.\n", + "\n", + "For vector fields, we also provide the index type to be used, and the metric. . Current options for index include \"**brute_force**\", \"**hnsw**\", \"**ivf**\", and \"**bin_ivf**\" for binary vectors, and \"**IP**\" (inner product) as a metric for floating point vectors and \"**Hamming**\" ([hamming distance](https://en.wikipedia.org/wiki/Hamming_distance)) for binary vectors.\n", + "Note that the key 'low_cardinality' enables faster search for low cardinality fields." + ], + "metadata": { + "id": "6BG-FyOlujHE" + }, + "id": "6BG-FyOlujHE" + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "976b2177", + "metadata": { + "id": "976b2177", + "ExecuteTime": { + "end_time": "2024-01-01T19:34:22.189609900Z", + "start_time": "2024-01-01T19:34:22.122809Z" + } + }, + "outputs": [], + "source": [ + "import json\n", + "vector_dimension = 800 # bits\n", + "config = {\n", + " \"configuration\": {\n", + " \"id\": {\n", + " \"type\": \"keyword\",\n", + " \"id\": True\n", + " },\n", + " 'city': {\"type\": 'keyword'},\n", + " 'country': {\"type\": 'keyword'},\n", + " 'open_now': {\"type\": 'boolean'},\n", + " 'zip_code': {\"type\": 'integer'},\n", + " 'street': {\"type\": 'keyword'},\n", + " 'vertical': {\"type\": 'keyword', 'low_cardinality': True},\n", + " \"vector\": {\n", + " \"type\": \"dense_vector\",\n", + " \"index_type\": \"bin_ivf\",\n", + " \"dim\": vector_dimension,\n", + " \"metric\": \"hamming\"\n", + " }\n", + " }\n", + "}\n", + "\n", + "with open('config.json', 'w') as f:\n", + " f.write(json.dumps(config, indent=2))\n" + ] + }, + { + "cell_type": "markdown", + "source": [ + "## 4. Create Collection\n", + "The Hyerspace engine stroes data in Collections, where each collecction commonly hosts data of similar context, etc. Each search is then perfomed within a collection. We create a collection using the command \"**create_collection**(schema_filename, collection_name)\"." + ], + "metadata": { + "id": "g1DHlx75uklY" + }, + "id": "g1DHlx75uklY" + }, + { + "cell_type": "code", + "source": [ + "collection_name = 'GeneratedData'\n", + "\n", + "if collection_name not in hyperspace_client.collections_info()[\"collections\"]:\n", + " hyperspace_client.create_collection('config.json', collection_name)\n", + "\n", + "hyperspace_client.collections_info()" + ], + "metadata": { + "id": "z43Vz3nabLZe", + "outputId": "3cfbf9e6-5b79-4bb3-fd30-76f7fe80f7b4", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "ExecuteTime": { + "end_time": "2024-01-01T19:34:22.583664500Z", + "start_time": "2024-01-01T19:34:22.149799700Z" + } + }, + "id": "z43Vz3nabLZe", + "execution_count": 6, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "{'collections': {'DocRetrievalEmbedded': {'creation_time': '2024-03-20T10:50:16Z',\n", + " 'last_query_time': '2024-03-25T09:27:27Z',\n", + " 'size': 39},\n", + " 'GeneratedData': {'creation_time': '2024-03-26T05:27:09Z',\n", + " 'last_query_time': '2024-03-26T06:24:53Z',\n", + " 'size': 100000}}}" + ] + }, + "metadata": {}, + "execution_count": 6 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "# 5. Ingest data\n", + "\n", + "In the next step we ingest the dataset in batches of 250 documents. This number can be controlled by user, and in particular, can be increased in order improve ingestion time. We add batches of data using the command **add_batch**(batch, collection_name)." + ], + "metadata": { + "id": "9eUT0cBRu31m" + }, + "id": "9eUT0cBRu31m" + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "import secrets\n", + "import base64\n", + "\n", + "def generate_data(metadata, vector_dimension):\n", + " data_point = random.choice(metadata)\n", + " random_bytes = secrets.token_bytes(vector_dimension // 8)\n", + " data_point['vector'] = base64.b64encode(random_bytes).decode()\n", + " return data_point" + ], + "metadata": { + "id": "_XCNBaIHLjZZ", + "ExecuteTime": { + "end_time": "2024-01-01T19:34:22.597661700Z", + "start_time": "2024-01-01T19:34:22.585667600Z" + } + }, + "id": "_XCNBaIHLjZZ", + "execution_count": 7, + "outputs": [] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Query run time: 2.43ms\n", - "[{'document_id': '65', 'score': 5.0}]\n" - ] + "cell_type": "code", + "source": [ + "pip install pandas requests\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "nnl5DAtITBbX", + "outputId": "246ac488-2883-4508-b204-b3387ce0766d" + }, + "id": "nnl5DAtITBbX", + "execution_count": 24, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (1.5.3)\n", + "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (2.31.0)\n", + "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas) (2.8.2)\n", + "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas) (2023.4)\n", + "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from pandas) (1.25.2)\n", + "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests) (3.3.2)\n", + "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests) (3.6)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests) (2.0.7)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests) (2024.2.2)\n", + "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n" + ] + } + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "95086784", + "metadata": { + "id": "95086784", + "ExecuteTime": { + "end_time": "2024-01-01T19:35:07.446200300Z", + "start_time": "2024-01-01T19:34:22.603667200Z" + } + }, + "outputs": [], + "source": [ + "import pickle\n", + "\n", + "data_path = 'Generated_data.hsv'\n", + "with open(data_path, 'rb') as file:\n", + " metadata = pickle.load(file)\n", + "\n", + "BATCH_SIZE = 250\n", + "\n", + "batch = []\n", + "data = []\n", + "\n", + "\n", + "for i, vec in enumerate(range(100000)):\n", + " data_point = generate_data(metadata, vector_dimension)\n", + " data_point[\"id\"] = str(i)\n", + " batch.append(dict(data_point))\n", + "\n", + " if (i+1) % BATCH_SIZE == 0:\n", + " response = hyperspace_client.add_batch(batch, collection_name)\n", + " print(i + 1, response)\n", + " batch.clear()\n", + "\n", + "if batch:\n", + " hyperspace_client.add_batch(batch, collection_name)\n", + " response = hyperspace_client.add_batch(batch, collection_name)\n", + "\n", + "hyperspace_client.commit(collection_name)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "source": [ + "#6. Define Logic and Run a Query\n", + "We will build a hybrid search query using Hyper-space. In the query, we will select a document and find similar ones. We must first compile the score function using the \"set_function\" command." + ], + "metadata": { + "id": "Yjo-yZwXDjkS" + }, + "id": "Yjo-yZwXDjkS" + }, + { + "cell_type": "code", + "source": [ + "import inspect\n", + "\n", + "def set_score_function(func, collection_name, score_function_name='func'):\n", + " source = inspect.getsource(func)\n", + " with open('sf.py', 'w') as f:\n", + " f.write(source)\n", + " hyperspace_client.set_function('sf.py', collection_name, score_function_name)\n" + ], + "metadata": { + "id": "Q-DQqoBpeETW", + "ExecuteTime": { + "end_time": "2024-01-01T19:35:07.490319600Z", + "start_time": "2024-01-01T19:35:07.450154700Z" + } + }, + "id": "Q-DQqoBpeETW", + "execution_count": 11, + "outputs": [] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "5c6e2ccb", + "metadata": { + "id": "5c6e2ccb", + "ExecuteTime": { + "end_time": "2024-01-01T19:35:08.570400500Z", + "start_time": "2024-01-01T19:35:07.465928200Z" + } + }, + "outputs": [], + "source": [ + "def similarity_score(params, doc):\n", + " score = 0.0\n", + " if match(\"country\"):\n", + " score = 5.0\n", + " if match(\"street\"):\n", + " score = 10.0\n", + " return score\n", + "\n", + "set_score_function(similarity_score, collection_name, score_function_name='similarity_score')" + ] + }, + { + "cell_type": "markdown", + "source": [ + "The next step is to retrieve a document and perform simialrity search." + ], + "metadata": { + "id": "RnQ4hgtueZ2j" + }, + "id": "RnQ4hgtueZ2j" + }, + { + "cell_type": "code", + "source": [ + "input_document = hyperspace_client.get_document(collection_name, 65)\n", + "input_document" + ], + "metadata": { + "id": "JpPhJG0wMsNg", + "outputId": "de3ec953-eb9d-4b1f-f4b9-1255dd3fb41e", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "ExecuteTime": { + "end_time": "2024-01-01T19:35:08.664430400Z", + "start_time": "2024-01-01T19:35:08.574444200Z" + } + }, + "id": "JpPhJG0wMsNg", + "execution_count": 13, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "{'city': 'Valerieport',\n", + " 'country': 'Maldives',\n", + " 'open_now': False,\n", + " 'zip_code': 11157,\n", + " 'vertical': 'xylophone',\n", + " 'vector': 'XojoT/WswsFMjLMX5p8tjUMDcWuGBX3GnBqPQUN/13unesI2n96T3c/vnE+eprGwtCX4ygyu3dSLC2PmPcUc3tlE8sm9VuSuf3gM64qv6St2tjBlcK2qBo/UPtUGXcRnlUD9rA==',\n", + " 'id': '65'}" + ] + }, + "metadata": {}, + "execution_count": 13 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Vector Search" + ], + "metadata": { + "id": "URXMq9eUHxKh" + }, + "id": "URXMq9eUHxKh" + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "5ff98e9d", + "metadata": { + "id": "5ff98e9d", + "outputId": "9ec098ca-e6b0-40d6-ebd8-203777f996c0", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "ExecuteTime": { + "end_time": "2024-01-01T19:35:08.757574300Z", + "start_time": "2024-01-01T19:35:08.664430400Z" + } + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Query run time: 1.90ms\n", + "[{'document_id': '10481', 'score': 357.0},\n", + " {'document_id': '48826', 'score': 357.0},\n", + " {'document_id': '61898', 'score': 357.0},\n", + " {'document_id': '80750', 'score': 357.0},\n", + " {'document_id': '65745', 'score': 356.0},\n", + " {'document_id': '62508', 'score': 354.0},\n", + " {'document_id': '85200', 'score': 354.0},\n", + " {'document_id': '9903', 'score': 354.0},\n", + " {'document_id': '12331', 'score': 353.0},\n", + " {'document_id': '29742', 'score': 353.0},\n", + " {'document_id': '79680', 'score': 352.0},\n", + " {'document_id': '63826', 'score': 350.0},\n", + " {'document_id': '34345', 'score': 347.0},\n", + " {'document_id': '41859', 'score': 338.0},\n", + " {'document_id': '65', 'score': 0.0}]\n" + ] + } + ], + "source": [ + "import random\n", + "from pprint import pprint\n", + "\n", + "\n", + "query_with_knn = {\n", + " 'params': input_document,\n", + " \"knn\": [{'field': \"vector\", 'boost': 1.0}]\n", + "}\n", + "\n", + "results = hyperspace_client.search(query_with_knn,\n", + " size=15,\n", + " collection_name=collection_name)\n", + "candidates = results['candidates']\n", + "\n", + "print(f\"Query run time: {results['took_ms']:.2f}ms\")\n", + "pprint(results['similarity'])\n" + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Results\n", + "The results are sorted by Hamming distance, as expected." + ], + "metadata": { + "id": "5lzGiQ3ON9bW" + }, + "id": "5lzGiQ3ON9bW" + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "ddd7d6a1", + "metadata": { + "id": "ddd7d6a1", + "outputId": "49a225f8-5e00-4e76-9b40-e3eb686f26db", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "ExecuteTime": { + "end_time": "2024-01-01T19:35:09.886289900Z", + "start_time": "2024-01-01T19:35:08.762573600Z" + } + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "0 {'city': 'South Alexandriaborough', 'country': 'Norway', 'open_now': True, 'zip_code': 24436, 'vertical': 'rainbow', 'vector': 'zbmrb+ImfooU/XHWHoAh1UcBpMQiBsdyTCE9BpA1HN0t8ybwjB+qhUbEbCqJuLH7U0amg1f9XSRcuQXmaR15HWXsiTRouCr7f/3cr9u/qQPOvYvK0Pj7HOG8LJc3c8FEhmbaGw==', 'id': '10481'}\n", + "1 {'city': 'West Brenda', 'country': 'Senegal', 'open_now': False, 'zip_code': 99714, 'street': 'banana', 'vector': '14EkJWFiA3TaWbXuexvICxNxeWAN8a4RgFokbREu8sfLwxzEggeHTFCniJSPDstmrSDIRE5+ERd0CYX/CKeKH0omxnO2ifUKkekWnoCD0C8sN5bqAkmX5uZGTtdcffQHVNOF7A==', 'id': '48826'}\n", + "2 {'city': 'North Markton', 'country': 'Mexico', 'open_now': True, 'zip_code': 15235, 'vertical': 'house', 'vector': 'wC3UHIUu5YoqnT1jdXAAtfMVP/3TpcPfXHheHgsHqYoSWibf2QIDlTALue/FRYYlJCAxyT0cmlSemGjs+hudM7pEg4hhZ/Li47kr6gi+gS3bJ9V4GHP+3C9OfF83lEIt7bCwPg==', 'id': '61898'}\n", + "3 {'city': 'Berryville', 'country': 'Costa Rica', 'open_now': True, 'zip_code': 70504, 'vector': 'EpNYUK4hlbhneymAh1IBreIq4fEo79H0VCHWLOIP56pLPNpHl7BmsxmumNeYihZ8vXU66kW5xeK+uzTeM+fKkERcNy2750SkZMnViwK3QqNBhaHjUAa4A4FCeWWTZZ3Y2O+3Xw==', 'id': '80750'}\n", + "4 {'city': 'Amberside', 'country': 'Honduras', 'open_now': False, 'zip_code': 43653, 'vector': 'jromyt5Ay8BIQFU58qe1rHUZmpuSb0q3TjMLHI23gBKF/UscjgQWw3aIU1fXy+U+9QTQSIOAfCXmkoLIHw8REhwH3uXzyCSAwYNVuzAspLqWZlx5MXyI8ZwUvvrfbK4tx6bejQ==', 'id': '65745'}\n", + "5 {'city': 'Candaceberg', 'country': 'Serbia', 'open_now': True, 'zip_code': 37172, 'vertical': 'umbrella', 'vector': '2mJRDKfwhhyIxifTr9IgxeTe7NKWrw0hobTqNEBoHmuA18J4m5adgB7Tv4vXdiU0h887z7D6+UUwQlxODd1USmhi/aEA/AR/xkNYWXufiFvunEprSQs6duMYqusFveQJckRzAQ==', 'id': '62508'}\n", + "6 {'city': 'South Lucasshire', 'country': 'Swaziland', 'open_now': False, 'zip_code': 56503, 'vertical': 'piano', 'vector': '5yhVFQ3swS1yZJD3s64mvEbWYCBttVZK7/BPPJVYI0a0dsDGuCytmcmSbNbanoBcPWf2tS2781czGbNPpS9R+TBJ8Fm9F42Kzf2oUlXJ7KOmh0fjvH/wut3KOlmQIE3kPgTZ/A==', 'id': '85200'}\n", + "7 {'city': 'Randolphville', 'country': 'Turkmenistan', 'open_now': False, 'zip_code': 33400, 'vector': 'nnmy6MCmWiOYvfiu3jFcXK30IxwaLluCKd/L4FEcBVJOr8XDAtNRDe7eG1YDiomw4husv2Doi0CZBu2wF8cw/VpS6RHkIvTIf8B1znAgoytF7ZHOIKz/XDleptMPqoStnwuYKg==', 'id': '9903'}\n", + "8 {'city': 'Morrisstad', 'country': 'Pakistan', 'open_now': False, 'zip_code': 82241, 'street': 'banana', 'vector': 'weIaSWP9SHFUQmLQ3Jlo/e+L8vlLZJWOXbzHVrEnuZfO4+MWK4bVjWCZLKO0RRWol17YzYTo3NIYQdSzPR9YUcBhwp+wldcalFEIGdf34cBskOVPGQLmC5rXNqcZ79coFpiIUQ==', 'id': '12331'}\n", + "9 {'city': 'Reginamouth', 'country': 'Kuwait', 'open_now': False, 'zip_code': 40156, 'street': 'ocean', 'vector': 'dsddzp1RhuUQHIl3xFSFqXCM5s4zQS32W0odxQkk2Ep0LH5QxtRZr0gTcIzlszuxhGt5TmpLD26YekanjMEAbA1DsimL2dToIyQEhQ5aiMartmNmPjA249+5cVPJMVwXuSwd7g==', 'id': '29742'}\n", + "10 {'city': 'Cochranhaven', 'country': 'Palau', 'open_now': True, 'zip_code': 97940, 'street': 'tiger', 'vector': 'PoiiJyifhc/vuY33c9u6Qd+i578fo8gq/cpplrp3nlv/06nT0m93AShP0pMh6HCdnbF5WSgDw4uvG3czeVgdYNrfMuedXeQJ42n8WoAvyu1W1E8EWMJDVb+QJ0VLjy7jpSpeLg==', 'id': '79680'}\n", + "11 {'city': 'South Paulbury', 'country': 'Timor-Leste', 'open_now': True, 'zip_code': 60407, 'street': 'rainbow', 'vector': 'Wbu6Z7IsH0fXxTBwkB4vi6PnMnqCkHihuJvQ2bCo8TmQ1fmi1o8Hmw6BzUG7fCHQuJh7kUsSt1e4OzzLXfyviOzGoqpB/vO4INw6aeie8q9RfsSWBW3LU8qQMMQbfyLLlTNr4A==', 'id': '63826'}\n", + "12 {'city': 'Knappshire', 'country': 'Bhutan', 'open_now': True, 'zip_code': 57177, 'vector': '2e52qRJ1cswHvznU7pmpDFtHoiSC110b/NoB3egK0DijNxH3kh6yMI+kImkmrCccBdU2ciWt+tzKidk7lbbwj/jQ7YXN16CoTOxh+xbJewuma+Wvss2O5ENT0sv9OMJPUYmhcA==', 'id': '34345'}\n", + "13 {'city': 'Barryport', 'country': 'South Georgia and the South Sandwich Islands', 'open_now': True, 'zip_code': 83769, 'street': 'rainbow', 'vector': 'jvplA+EtAr1JrFYfTgOvC4OZ+uPiUu413BjRzUtaZOvmRosxnA8oo+m6DUNXoNkh1txfeO2HLM8Zgh4qJ98K2uKYuNv5DzAwXH8AY2hFlQDdm5bcedgCtT7UZPiipbVNlWK6gA==', 'id': '41859'}\n", + "14 {'city': 'Valerieport', 'country': 'Maldives', 'open_now': False, 'zip_code': 11157, 'vertical': 'xylophone', 'vector': 'XojoT/WswsFMjLMX5p8tjUMDcWuGBX3GnBqPQUN/13unesI2n96T3c/vnE+eprGwtCX4ygyu3dSLC2PmPcUc3tlE8sm9VuSuf3gM64qv6St2tjBlcK2qBo/UPtUGXcRnlUD9rA==', 'id': '65'}\n" + ] + } + ], + "source": [ + "for i, x in enumerate(results['similarity']):\n", + " document = hyperspace_client.get_document(collection_name, x[\"document_id\"])\n", + " print(i, document)" + ] + }, + { + "cell_type": "markdown", + "source": [ + "#Hybrid Search\n", + "In the next step, we will perform Hybrid Search using two methods. In the first method, we will combine a classic score function with vector search through a linear combination of the scores. In the second method, we will use a Hybrid score function. In both methods we will use the pre-filtering approach, determined by the indexing method in the config schema file.\n", + "\n", + "## Hybrid Search Using Linear Combination of Scores" + ], + "metadata": { + "id": "sd6AQ5Y3IEaH" + }, + "id": "sd6AQ5Y3IEaH" + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "from pprint import pprint\n", + "\n", + "\n", + "query_with_knn = {\n", + " 'params': input_document,\n", + " \"knn\": [{'field': \"vector\", 'boost': 1.0},\n", + " {'field': \"query\", 'boost': 0.1}]\n", + "}\n", + "\n", + "results = hyperspace_client.search(query_with_knn,\n", + " size=15,\n", + " function_name='similarity_score',\n", + " collection_name=collection_name)\n", + "candidates = results['candidates']\n", + "\n", + "print(f\"Query run time: {results['took_ms']:.2f}ms\")\n", + "pprint(results['similarity'])\n" + ], + "metadata": { + "id": "m6pMqw6NIH_K", + "ExecuteTime": { + "end_time": "2024-01-01T19:35:09.979062300Z", + "start_time": "2024-01-01T19:35:09.889289800Z" + }, + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "3f4422a7-90ec-4a27-c655-b0812cfb4438" + }, + "id": "m6pMqw6NIH_K", + "execution_count": 16, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Query run time: 2.71ms\n", + "[{'document_id': '1107', 'score': 0.5},\n", + " {'document_id': '1304', 'score': 0.5},\n", + " {'document_id': '1437', 'score': 0.5},\n", + " {'document_id': '1607', 'score': 0.5},\n", + " {'document_id': '1769', 'score': 0.5},\n", + " {'document_id': '1882', 'score': 0.5},\n", + " {'document_id': '2151', 'score': 0.5},\n", + " {'document_id': '312', 'score': 0.5},\n", + " {'document_id': '422', 'score': 0.5},\n", + " {'document_id': '459', 'score': 0.5},\n", + " {'document_id': '65', 'score': 0.5},\n", + " {'document_id': '696', 'score': 0.5},\n", + " {'document_id': '822', 'score': 0.5},\n", + " {'document_id': '825', 'score': 0.5},\n", + " {'document_id': '982', 'score': 0.5}]\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Hybrid Search Using Hybrid Score Function\n", + "The following function combines a classic score and manual boost with vector score." + ], + "metadata": { + "id": "PwtApSv-Y8yW" + }, + "id": "PwtApSv-Y8yW" + }, + { + "cell_type": "code", + "source": [ + "def hybrid_similarity_score(params, doc):\n", + " score = 0.0\n", + " boost = 1.0\n", + " if match(\"country\"):\n", + " score = 5.0\n", + " boost = 2.0\n", + " if match(\"street\"):\n", + " score = 10.0\n", + " return score + boost * distance(\"vector\")\n", + "\n", + "set_score_function(hybrid_similarity_score, collection_name, score_function_name='hybrid_similarity_score')" + ], + "metadata": { + "id": "GKgiEhC5bKwV" + }, + "id": "GKgiEhC5bKwV", + "execution_count": 22, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "from pprint import pprint\n", + "\n", + "\n", + "query_with_knn = {\n", + " 'params': input_document\n", + "}\n", + "\n", + "results = hyperspace_client.search(query_with_knn,\n", + " size=15,\n", + " function_name='hybrid_similarity_score',\n", + " collection_name=collection_name)\n", + "candidates = results['candidates']\n", + "\n", + "print(f\"Query run time: {results['took_ms']:.2f}ms\")\n", + "pprint(results['similarity'])\n" + ], + "metadata": { + "id": "Q-jYAsUca2aW", + "outputId": "b4258a21-ff98-45f7-c03f-711e505a982c", + "colab": { + "base_uri": "https://localhost:8080/" + } + }, + "id": "Q-jYAsUca2aW", + "execution_count": 23, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Query run time: 3.00ms\n", + "[{'document_id': '1107', 'score': 5.0},\n", + " {'document_id': '1304', 'score': 5.0},\n", + " {'document_id': '1437', 'score': 5.0},\n", + " {'document_id': '1607', 'score': 5.0},\n", + " {'document_id': '1769', 'score': 5.0},\n", + " {'document_id': '1882', 'score': 5.0},\n", + " {'document_id': '2151', 'score': 5.0},\n", + " {'document_id': '312', 'score': 5.0},\n", + " {'document_id': '422', 'score': 5.0},\n", + " {'document_id': '459', 'score': 5.0},\n", + " {'document_id': '65', 'score': 5.0},\n", + " {'document_id': '696', 'score': 5.0},\n", + " {'document_id': '822', 'score': 5.0},\n", + " {'document_id': '825', 'score': 5.0},\n", + " {'document_id': '982', 'score': 5.0}]\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "This notebook gave a simple example of the use of the Hyperspace engine for hybrid search. Hyperspace can support signficantly more complicated use cases with large databases, in extremley low latency." + ], + "metadata": { + "id": "HHUPLwHjNE67" + }, + "id": "HHUPLwHjNE67" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.13" + }, + "colab": { + "provenance": [] } - ] - }, - { - "cell_type": "markdown", - "source": [ - "This notebook gave a simple example of the use of the Hyperspace engine for hybrid search. Hyperspace can support signficantly more complicated use cases with large databases, in extremley low latency." - ], - "metadata": { - "id": "HHUPLwHjNE67" - }, - "id": "HHUPLwHjNE67" - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" }, - "colab": { - "provenance": [] - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file