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[Database & ORM](/categories/database) 4. / 5. mindfulcoder49/mysql-vector-openai ActiveLibrary[Database & ORM](/categories/database) mindfulcoder49/mysql-vector-openai ================================== Perform vector operations natively on MySQL using openAI embeddings 1.0.2(1y ago)016MITPHPPHP >=8.0 Since Sep 10Pushed 1y agoCompare [ Source](https://github.com/mindfulcoder49/mysql-vector-openai)[ Packagist](https://packagist.org/packages/mindfulcoder49/mysql-vector-openai)[ RSS](/packages/mindfulcoder49-mysql-vector-openai/feed)WikiDiscussions main Synced 1mo ago READMEChangelogDependencies (6)Versions (4)Used By (0) Here's a `README.md` file that reflects the current functionality of your `VectorTable` class. ``` # MySQL Vector Table This repository provides an implementation for storing, searching, and manipulating vectors in a MySQL database using cosine similarity and binary codes for efficient search. The main class `VectorTable` provides a variety of functions to handle vector data, including inserting, updating, searching, and computing similarity between vectors. ## Features - **Cosine Similarity Search (COSIM)**: Efficiently compute the cosine similarity between vectors stored as JSON in MySQL. - **Binary Code Representation**: Vectors are stored in binary form for efficient querying and similarity computation. - **Hamming Distance Search (Optional)**: A method for searching vectors based on Hamming distance is also available, though not the primary method. - **Vector Normalization**: Automatically normalizes vectors before inserting and computing similarity. - **Batch Insertion**: Support for inserting multiple vectors at once. - **Vector Management**: Functions to insert, update, delete, and retrieve vectors. ## Table Structure The vectors are stored in a MySQL table with the following structure: ```sql CREATE TABLE `your_table_name_vectors` ( `id` INT UNSIGNED AUTO_INCREMENT PRIMARY KEY, `vector` JSON, -- The original vector `normalized_vector` JSON, -- The normalized vector `magnitude` DOUBLE, -- The magnitude of the vector `binary_code` BLOB, -- Binary representation of the vector for efficient searching `created` TIMESTAMP DEFAULT CURRENT_TIMESTAMP ) ENGINE=InnoDB; ``` MySQL Function: `COSIM` ----------------------- [](#mysql-function-cosim) The class defines a custom MySQL function `COSIM` to compute cosine similarity between two vectors stored as JSON. ``` CREATE FUNCTION COSIM(v1 JSON, v2 JSON) RETURNS FLOAT DETERMINISTIC BEGIN DECLARE sim FLOAT DEFAULT 0; DECLARE i INT DEFAULT 0; DECLARE len INT DEFAULT JSON_LENGTH(v1); IF JSON_LENGTH(v1) != JSON_LENGTH(v2) THEN RETURN NULL; END IF; WHILE i search($inputVector, $n = 10); ``` - **$inputVector**: The vector to compare against the stored vectors. - **$n**: The number of results to return (default is 10). The function returns an array of the most similar vectors sorted by cosine similarity. ### `searchWithHamming()` [](#searchwithhamming) Search for vectors in the table based on Hamming distance between binary representations of vectors. #### Usage: [](#usage-1) ``` $results = $vectorTable->searchWithHamming($inputVector, $n = 10); ``` ### `upsert()` [](#upsert) Insert or update a vector in the table. If the vector already exists (based on ID), it will be updated. Otherwise, a new vector will be inserted. #### Usage: [](#usage-2) ``` $id = $vectorTable->upsert($vector, $id = null); ``` - **$vector**: The vector to insert or update. - **$id**: The optional ID of the vector to update. If not provided, a new vector is inserted. ### `batchInsert()` [](#batchinsert) Insert multiple vectors into the table in a single transaction. #### Usage: [](#usage-3) ``` $ids = $vectorTable->batchInsert($vectorArray); ``` - **$vectorArray**: An array of vectors to be inserted. ### `select()` [](#select) Retrieve vectors from the table by their IDs. #### Usage: [](#usage-4) ``` $vectors = $vectorTable->select($ids); ``` - **$ids**: An array of vector IDs to retrieve. ### `selectAll()` [](#selectall) Retrieve all vectors from the table. #### Usage: [](#usage-5) ``` $vectors = $vectorTable->selectAll(); ``` ### `delete()` [](#delete) Remove a vector from the table by its ID. #### Usage: [](#usage-6) ``` $vectorTable->delete($id); ``` - **$id**: The ID of the vector to remove. ### `normalize()` [](#normalize) Normalize a vector by its magnitude. #### Usage: [](#usage-7) ``` $normalizedVector = $vectorTable->normalize($vector); ``` - **$vector**: The vector to normalize. ### `cosim()` [](#cosim) Compute the cosine similarity between two vectors. #### Usage: [](#usage-8) ``` $similarity = $vectorTable->cosim($v1, $v2); ``` - **$v1**: The first vector. - **$v2**: The second vector. ### `count()` [](#count) Get the total number of vectors stored in the database. #### Usage: [](#usage-9) ``` $totalVectors = $vectorTable->count(); ``` ### `vectorToBinary()` [](#vectortobinary) Convert an n-dimensional vector into a binary code. #### Usage: [](#usage-10) ``` $binaryCode = $vectorTable->vectorToBinary($vector); ``` Initialization -------------- [](#initialization) To create the necessary tables and functions, you need to call the `initialize()` method. ``` $vectorTable->initialize(); ``` This will create the vectors table and the cosine similarity function (`COSIM`) in your database. Installation ------------ [](#installation) 1. Set up a MySQL database. 2. Create an instance of the `VectorTable` class. 3. Call `initialize()` to set up the table and functions. 4. Start inserting, updating, and searching for vectors! ### Example: [](#example) ``` $mysqli = new \mysqli('localhost', 'user', 'password', 'database'); $vectorTable = new \MHz\MysqlVector\VectorTable($mysqli, 'example_table', 384); $vectorTable->initialize(); $vector = [1, 2, 3, 4, 5]; $vectorTable->upsert($vector); $similarVectors = $vectorTable->search($vector); ``` License ------- [](#license) This project is licensed under the MIT License. ``` This `README.md` outlines the features, core functionalities, usage examples, and setup instructions for your `VectorTable` class. It reflects the current state of your code, including both cosine similarity and Hamming distance-based searches, and explains how to initialize, insert, search, and manage vectors in the MySQL database. ``` ### Health Score 26 — LowBetter than 43% of packages Maintenance35 Infrequent updates — may be unmaintained Popularity6 Limited adoption so far Community8 Small or concentrated contributor base Maturity46 Maturing project, gaining track record Bus Factor1 Top contributor holds 84.4% of commits — single point of failure How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window. **Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores. **Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement. **Maturity (30%)** — Project age, version count, PHP version support, and release stability. ### Release Activity Cadence Every ~3 days Total 3 Last Release 609d ago ### Community Maintainers ![](https://www.gravatar.com/avatar/c5b68c1f0b87e8833ff11536cc69e10ac86f6fc5ab162dfc93a473898f212156?d=identicon)[mindfulcoder49](/maintainers/mindfulcoder49) --- Top Contributors [![allanpichardo](https://avatars.githubusercontent.com/u/5606153?v=4)](https://github.com/allanpichardo "allanpichardo (27 commits)")[![mindfulcoder49](https://avatars.githubusercontent.com/u/132383684?v=4)](https://github.com/mindfulcoder49 "mindfulcoder49 (5 commits)") ### Code Quality TestsPHPUnit ### Embed Badge ![Health badge](/badges/mindfulcoder49-mysql-vector-openai/health.svg) ``` [![Health](https://phpackages.com/badges/mindfulcoder49-mysql-vector-openai/health.svg)](https://phpackages.com/packages/mindfulcoder49-mysql-vector-openai) ``` ### Alternatives [symfony/symfony The Symfony PHP framework 31.3k86.3M2.2k](/packages/symfony-symfony)[symfony/string Provides an object-oriented API to strings and deals with bytes, UTF-8 code points and grapheme clusters in a unified way 1.8k724.1M827](/packages/symfony-string)[twig/twig Twig, the flexible, fast, and secure template language for PHP 8.4k443.2M5.8k](/packages/twig-twig)[symfony/filesystem Provides basic utilities for the filesystem 4.6k669.1M3.2k](/packages/symfony-filesystem)[symfony/dom-crawler Eases DOM navigation for HTML and XML documents 4.0k379.0M2.2k](/packages/symfony-dom-crawler)[symfony/validator Provides tools to validate values 2.7k287.3M3.3k](/packages/symfony-validator) PHPackages © 2026 [Directory](/)[Categories](/categories)[Trending](/trending)[Changelog](/changelog)[Analyze](/analyze)