
laravel-slower
★ Laravel Slower: Optimize Your DB Queries with AI
Stars: 284

Laravel Slower is a powerful package designed for Laravel developers to optimize the performance of their applications by identifying slow database queries and providing AI-driven suggestions for optimal indexing strategies and performance improvements. It offers actionable insights for debugging and monitoring database interactions, enhancing efficiency and scalability.
README:
Laravel Slower is a powerful package designed for Laravel developers who want to enhance the performance of their applications. It intelligently identifies slow database queries and leverages AI to suggest optimal indexing strategies and other performance improvements. Whether you're debugging or routinely monitoring your application, Laravel Slower provides actionable insights to streamline database interactions.
You can install the package via composer:
composer require halilcosdu/laravel-slower
You can publish the config file with:
php artisan vendor:publish --tag="slower-config"
This is the contents of the published config file:
You can disable AI recommendations by setting the ai_recommendation
key to false
in the config file. If you disable AI recommendations, the package will not make any API requests to OpenAI.
<?php
// config for HalilCosdu/Slower
use HalilCosdu\Slower\Models\SlowLog;
return [
'enabled' => env('SLOWER_ENABLED', true),
'threshold' => env('SLOWER_THRESHOLD', 10000),
'resources' => [
'table_name' => (new SlowLog)->getTable(),
'model' => SlowLog::class,
],
'ai_recommendation' => env('SLOWER_AI_RECOMMENDATION', true),
'recommendation_model' => env('SLOWER_AI_RECOMMENDATION_MODEL', 'gpt-4'),
'recommendation_use_explain' => env('SLOWER_AI_RECOMMENDATION_USE_EXPLAIN', true),
'ignore_explain_queries' => env('SLOWER_IGNORE_EXPLAIN_QUERIES', true),
'ignore_insert_queries' => env('SLOWER_IGNORE_INSERT_QUERIES', true),
'open_ai' => [
'api_key' => env('OPENAI_API_KEY'),
'organization' => env('OPENAI_ORGANIZATION'),
'request_timeout' => env('OPENAI_TIMEOUT'),
],
'prompt' => env('SLOWER_PROMPT', 'As a distinguished database optimization expert, your expertise is invaluable for refining SQL queries to achieve maximum efficiency. Schema json provide list of indexes and column definitions for each table in query. Also analyse the output of EXPLAIN ANALYSE and provide recommendations to optimize query. Please examine the SQL statement provided below including EXPLAIN ANALYSE query plan. Based on your analysis, could you recommend sophisticated indexing techniques or query modifications that could significantly improve performance and scalability?'),
];
You can publish and run the migrations with:
php artisan vendor:publish --tag="slower-migrations"
php artisan migrate
public function up()
{
Schema::create(config('slower.resources.table_name'), function (Blueprint $table) {
$table->id();
$table->boolean('is_analyzed')->default(false)->index();
$table->longtext('bindings');
$table->longtext('sql');
$table->float('time')->nullable()->index();
$table->string('connection');
$table->string('connection_name')->nullable();
$table->longtext('raw_sql');
$table->longtext('recommendation')->nullable();
$table->timestamps();
});
}
public function down(): void
{
Schema::dropIfExists(config('slower.resources.table_name'));
}
You can register the commands with your scheduler.
php artisan slower:clean /*{days=15} Delete records older than 15 days.*/
php artisan slower:analyze /*Analyze the records where is_analyzed=false*/
use HalilCosdu\Slower\Commands\AnalyzeQuery;
use HalilCosdu\Slower\Commands\SlowLogCleaner;
protected $commands = [
AnalyzeQuery::class,
SlowLogCleaner::class,
];
/**
* Define the application's command schedule.
*/
protected function schedule(Schedule $schedule): void
{
$schedule->command(AnalyzeQuery::class)->runInBackground()->daily();
$schedule->command(SlowLogCleaner::class)->runInBackground()->daily();
}
$model = \HalilCosdu\Slower\Models\SlowLog::first();
\HalilCosdu\Slower\Facades\Slower::analyze($model): Model;
dd($model->raw_sql); /*select count(*) as aggregate from "product_prices" where "product_id" = '1' and "price" = '0' and "discount_total" > '0'*/
dd($model->recommendation);
In order to improve database performance and scalability, here are some suggestions below:
- Indexing: Effective database indexing can significantly speed up query performance. For your query, consider adding a combined (composite) index on
product_id
,price
, anddiscount_total
. This index would work well because the where clause covers all these columns.
CREATE INDEX idx_product_prices
ON product_prices (product_id, price, discount_total);
(Note: The order of the columns in the index might depend on the selectivity of the columns and the data distribution. Therefore, you might have to reorder them depending on your specific situation.)
- Data Types: Ensure that the values being compared are of appropriate data types. Comparing or converting inappropriate data types at run time will slow down the search. It appears that you're using string comparisons ('1') for
product_id
,price
, anddiscount_total
which are likely numerical columns. Remove the quotes for these where clause conditions.
Updated Query:
SELECT COUNT(*) AS aggregate
FROM product_prices
WHERE product_id = 1
AND price = 0
AND discount_total > 0;
- ANALYZE: Another practice to improve query performance could be running the
ANALYZE
command. This command collects statistics about the contents of tables in the database, and stores the results in the pg_statistic system catalog. Subsequently, the query planner uses these statistics to help determine the most efficient execution plans for queries.
ANALYZE product_prices;
Remember to periodically maintain your index to keep up with the CRUD operations that could lead to index fragmentation. Depending on your DBMS, you might want to REBUILD or REORGANIZE your indices.
composer test
- [ ] Create a documentation page.
- [ ] Begin development of version 2.
- [ ] Auto Indexer (Premium Feature)
- [ ] Create a FilamentPHP plugin.
Please see CHANGELOG for more information on what has changed recently.
Please see CONTRIBUTING for details.
Please review our security policy on how to report security vulnerabilities.
The MIT License (MIT). Please see License File for more information.
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for laravel-slower
Similar Open Source Tools

laravel-slower
Laravel Slower is a powerful package designed for Laravel developers to optimize the performance of their applications by identifying slow database queries and providing AI-driven suggestions for optimal indexing strategies and performance improvements. It offers actionable insights for debugging and monitoring database interactions, enhancing efficiency and scalability.

LarAgent
LarAgent is a framework designed to simplify the creation and management of AI agents within Laravel projects. It offers an Eloquent-like syntax for creating and managing AI agents, Laravel-style artisan commands, flexible agent configuration, structured output handling, image input support, and extensibility. LarAgent supports multiple chat history storage options, custom tool creation, event system for agent interactions, multiple provider support, and can be used both in Laravel and standalone environments. The framework is constantly evolving to enhance developer experience, improve AI capabilities, enhance security and storage features, and enable advanced integrations like provider fallback system, Laravel Actions integration, and voice chat support.

extractor
Extractor is an AI-powered data extraction library for Laravel that leverages OpenAI's capabilities to effortlessly extract structured data from various sources, including images, PDFs, and emails. It features a convenient wrapper around OpenAI Chat and Completion endpoints, supports multiple input formats, includes a flexible Field Extractor for arbitrary data extraction, and integrates with Textract for OCR functionality. Extractor utilizes JSON Mode from the latest GPT-3.5 and GPT-4 models, providing accurate and efficient data extraction.

IntelliNode
IntelliNode is a javascript module that integrates cutting-edge AI models like ChatGPT, LLaMA, WaveNet, Gemini, and Stable diffusion into projects. It offers functions for generating text, speech, and images, as well as semantic search, multi-model evaluation, and chatbot capabilities. The module provides a wrapper layer for low-level model access, a controller layer for unified input handling, and a function layer for abstract functionality tailored to various use cases.

lollms
LoLLMs Server is a text generation server based on large language models. It provides a Flask-based API for generating text using various pre-trained language models. This server is designed to be easy to install and use, allowing developers to integrate powerful text generation capabilities into their applications.

LightRAG
LightRAG is a PyTorch library designed for building and optimizing Retriever-Agent-Generator (RAG) pipelines. It follows principles of simplicity, quality, and optimization, offering developers maximum customizability with minimal abstraction. The library includes components for model interaction, output parsing, and structured data generation. LightRAG facilitates tasks like providing explanations and examples for concepts through a question-answering pipeline.

flutter_gemma
Flutter Gemma is a family of lightweight, state-of-the art open models that bring the power of Google's Gemma language models directly to Flutter applications. It allows for local execution on user devices, supports both iOS and Android platforms, and offers LoRA support for tailored AI behavior. The tool provides a simple interface for integrating Gemma models into Flutter projects, enabling advanced AI capabilities without relying on external servers. Users can easily download pre-trained Gemma models, fine-tune them for specific use cases, and customize behavior using LoRA weights. The tool supports model and LoRA weight management, model initialization, response generation, and chat scenarios, with considerations for model size, LoRA weights, and production app deployment.

llm-chain
LLM Chain is a PHP library for building LLM-based features and applications. It provides abstractions for Language Models and Embeddings Models from platforms like OpenAI, Azure, Google, Replicate, and others. The core feature is to interact with language models via messages, supporting different message types and content. LLM Chain also supports tool calling, document embedding, vector stores, similarity search, structured output, response streaming, image processing, audio processing, embeddings, parallel platform calls, and input/output processing. Contributions are welcome, and the repository contains fixture licenses for testing multi-modal features.

litdata
LitData is a tool designed for blazingly fast, distributed streaming of training data from any cloud storage. It allows users to transform and optimize data in cloud storage environments efficiently and intuitively, supporting various data types like images, text, video, audio, geo-spatial, and multimodal data. LitData integrates smoothly with frameworks such as LitGPT and PyTorch, enabling seamless streaming of data to multiple machines. Key features include multi-GPU/multi-node support, easy data mixing, pause & resume functionality, support for profiling, memory footprint reduction, cache size configuration, and on-prem optimizations. The tool also provides benchmarks for measuring streaming speed and conversion efficiency, along with runnable templates for different data types. LitData enables infinite cloud data processing by utilizing the Lightning.ai platform to scale data processing with optimized machines.

clarifai-python-grpc
This is the official Clarifai gRPC Python client for interacting with their recognition API. Clarifai offers a platform for data scientists, developers, researchers, and enterprises to utilize artificial intelligence for image, video, and text analysis through computer vision and natural language processing. The client allows users to authenticate, predict concepts in images, and access various functionalities provided by the Clarifai API. It follows a versioning scheme that aligns with the backend API updates and includes specific instructions for installation and troubleshooting. Users can explore the Clarifai demo, sign up for an account, and refer to the documentation for detailed information.

rl
TorchRL is an open-source Reinforcement Learning (RL) library for PyTorch. It provides pytorch and **python-first** , low and high level abstractions for RL that are intended to be **efficient** , **modular** , **documented** and properly **tested**. The code is aimed at supporting research in RL. Most of it is written in python in a highly modular way, such that researchers can easily swap components, transform them or write new ones with little effort.

raid
RAID is the largest and most comprehensive dataset for evaluating AI-generated text detectors. It contains over 10 million documents spanning 11 LLMs, 11 genres, 4 decoding strategies, and 12 adversarial attacks. RAID is designed to be the go-to location for trustworthy third-party evaluation of popular detectors. The dataset covers diverse models, domains, sampling strategies, and attacks, making it a valuable resource for training detectors, evaluating generalization, protecting against adversaries, and comparing to state-of-the-art models from academia and industry.

react-native-fast-tflite
A high-performance TensorFlow Lite library for React Native that utilizes JSI for power, zero-copy ArrayBuffers for efficiency, and low-level C/C++ TensorFlow Lite core API for direct memory access. It supports swapping out TensorFlow Models at runtime and GPU-accelerated delegates like CoreML/Metal/OpenGL. Easy VisionCamera integration allows for seamless usage. Users can load TensorFlow Lite models, interpret input and output data, and utilize GPU Delegates for faster computation. The library is suitable for real-time object detection, image classification, and other machine learning tasks in React Native applications.

amadeus-python
Amadeus Python SDK provides a rich set of APIs for the travel industry. It allows users to make API calls for various travel-related tasks such as flight offers search, hotel bookings, trip purpose prediction, flight delay prediction, airport on-time performance, travel recommendations, and more. The SDK conveniently maps API paths to similar paths, making it easy to interact with the Amadeus APIs. Users can initialize the client with their API key and secret, make API calls, handle responses, and enable logging for debugging purposes. The SDK documentation includes detailed information about each SDK method, arguments, and return types.

suno-api
Suno AI API is an open-source project that allows developers to integrate the music generation capabilities of Suno.ai into their own applications. The API provides a simple and convenient way to generate music, lyrics, and other audio content using Suno.ai's powerful AI models. With Suno AI API, developers can easily add music generation functionality to their apps, websites, and other projects.

pebblo
Pebblo enables developers to safely load data and promote their Gen AI app to deployment without worrying about the organization’s compliance and security requirements. The project identifies semantic topics and entities found in the loaded data and summarizes them on the UI or a PDF report.
For similar tasks

laravel-slower
Laravel Slower is a powerful package designed for Laravel developers to optimize the performance of their applications by identifying slow database queries and providing AI-driven suggestions for optimal indexing strategies and performance improvements. It offers actionable insights for debugging and monitoring database interactions, enhancing efficiency and scalability.

ChatDev
ChatDev is a virtual software company powered by intelligent agents like CEO, CPO, CTO, programmer, reviewer, tester, and art designer. These agents collaborate to revolutionize the digital world through programming. The platform offers an easy-to-use, highly customizable, and extendable framework based on large language models, ideal for studying collective intelligence. ChatDev introduces innovative methods like Iterative Experience Refinement and Experiential Co-Learning to enhance software development efficiency. It supports features like incremental development, Docker integration, Git mode, and Human-Agent-Interaction mode. Users can customize ChatChain, Phase, and Role settings, and share their software creations easily. The project is open-source under the Apache 2.0 License and utilizes data licensed under CC BY-NC 4.0.

THE-SANDBOX-AutoClicker
The Sandbox AutoClicker is a bot designed for the crypto game The Sandbox, allowing users to automate various processes within the game. The tool offers features such as auto tuning, multi-account auto clicker, multi-threading, a convenient menu, and free proxies. It provides full optimization through a simple menu and is guaranteed to be safe for Windows systems, supporting versions 7/8/8.1/10/11 (x32/64).

Awesome-LLM-Prune
This repository is dedicated to the pruning of large language models (LLMs). It aims to serve as a comprehensive resource for researchers and practitioners interested in the efficient reduction of model size while maintaining or enhancing performance. The repository contains various papers, summaries, and links related to different pruning approaches for LLMs, along with author information and publication details. It covers a wide range of topics such as structured pruning, unstructured pruning, semi-structured pruning, and benchmarking methods. Researchers and practitioners can explore different pruning techniques, understand their implications, and access relevant resources for further study and implementation.

SuperCoder
SuperCoder is an open-source autonomous software development system that leverages advanced AI tools and agents to streamline and automate coding, testing, and deployment tasks, enhancing efficiency and reliability. It supports a variety of languages and frameworks for diverse development needs. Users can set up the environment variables, build and run the Go server, Asynq worker, and Postgres using Docker and Docker Compose. The project is under active development and may still have issues, but users can seek help and support from the Discord community or by creating new issues on GitHub.

MoBA
MoBA (Mixture of Block Attention) is an innovative approach for long-context language models, enabling efficient processing of long sequences by dividing the full context into blocks and introducing a parameter-less gating mechanism. It allows seamless transitions between full and sparse attention modes, enhancing efficiency without compromising performance. MoBA has been deployed to support long-context requests and demonstrates significant advancements in efficient attention computation for large language models.

aiges
AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.

holoinsight
HoloInsight is a cloud-native observability platform that provides low-cost and high-performance monitoring services for cloud-native applications. It offers deep insights through real-time log analysis and AI integration. The platform is designed to help users gain a comprehensive understanding of their applications' performance and behavior in the cloud environment. HoloInsight is easy to deploy using Docker and Kubernetes, making it a versatile tool for monitoring and optimizing cloud-native applications. With a focus on scalability and efficiency, HoloInsight is suitable for organizations looking to enhance their observability and monitoring capabilities in the cloud.
For similar jobs

lollms-webui
LoLLMs WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all) is a user-friendly interface to access and utilize various LLM (Large Language Models) and other AI models for a wide range of tasks. With over 500 AI expert conditionings across diverse domains and more than 2500 fine tuned models over multiple domains, LoLLMs WebUI provides an immediate resource for any problem, from car repair to coding assistance, legal matters, medical diagnosis, entertainment, and more. The easy-to-use UI with light and dark mode options, integration with GitHub repository, support for different personalities, and features like thumb up/down rating, copy, edit, and remove messages, local database storage, search, export, and delete multiple discussions, make LoLLMs WebUI a powerful and versatile tool.

Azure-Analytics-and-AI-Engagement
The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

minio
MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.

mage-ai
Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.

AiTreasureBox
AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.

tidb
TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

airbyte
Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.

labelbox-python
Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.