Best AI tools for< Optimize Code Splitting >

GitBrain is an AI-powered Git client designed for Mac users. It simplifies the Git workflow by offering features such as AI commit messages, code splitting, self code review, auto-detection of projects from favorite IDEs, and a keyboard-friendly design. The application aims to make developers more productive by intelligently handling Git operations and providing a seamless user experience. GitBrain is optimized for Mac performance with a native UI and offers light & dark mode themes for customization.

Code to Flowchart is an AI-powered tool that helps users visualize and understand program logic instantly. It allows users to convert code into interactive flowcharts with the help of AI analysis. The tool supports all major programming languages, identifies code paths and logic flows, and offers multiple visualization options like flowcharts, sequence diagrams, and class diagrams. Users can export diagrams in various formats and customize color schemes and themes. Code to Flowchart aims to simplify complex code structures and enhance collaboration among developers.

Code & Pepper is an elite software development company specializing in FinTech and HealthTech. They combine human talent with AI tools to deliver efficient solutions. With a focus on specific technologies like React.js, Node.js, Angular, Ruby on Rails, and React Native, they offer custom software products and dedicated software engineers. Their unique talent identification methodology selects the top 1.6% of candidates for exceptional outcomes. Code & Pepper champions human-AI centaur teams, harmonizing creativity with AI precision for superior results.

CodeRabbit is an innovative AI code review platform that streamlines and enhances the development process. By automating reviews, it dramatically improves code quality while saving valuable time for developers. The system offers detailed, line-by-line analysis, providing actionable insights and suggestions to optimize code efficiency and reliability. Trusted by hundreds of organizations and thousands of developers daily, CodeRabbit has processed millions of pull requests. Backed by CRV, CodeRabbit continues to revolutionize the landscape of AI-assisted software development.

Codacy is an AI-powered code quality and security platform designed for developers to efficiently optimize and secure their code. It offers a unified set of AppSec tools, data-driven insights, and seamless integrations across the software development lifecycle. Codacy helps teams monitor and resolve security issues at scale, improve code quality, and prevent breaking changes. With AI suggested fixes and effortless code quality monitoring, Codacy is a valuable tool for businesses and developers alike.

Safurai is an AI-powered coding assistant that helps developers write code faster, safer, and better. It offers a range of features, including a textbox for asking questions and getting code suggestions, shortcuts for code optimization and unit testing, the ability to train the assistant on specific projects, and a natural language search for finding code. Safurai is compatible with various IDEs, including Visual Studio Code, IntelliJ, and PyCharm.

AICodeConvert is an AI tool that simplifies coding by integrating AI Code Translator and AI Code Generator. It efficiently translates existing code into different programming languages and automatically generates high-quality code snippets and templates. This powerful combination makes AICodeConvert an indispensable tool for developers, providing a convenient and intelligent coding experience.

Smaty.xyz is a comprehensive platform that provides a suite of tools for code generation and security auditing. With Smaty.xyz, developers can quickly and easily generate high-quality code in multiple programming languages, ensuring consistency and reducing development time. Additionally, Smaty.xyz offers robust security auditing capabilities, enabling developers to identify and address vulnerabilities in their code, mitigating risks and enhancing the overall security of their applications.

Kodezi is an AI-powered development tool that helps developers write better code. It offers a range of features to help developers with tasks such as code autocorrect, code review, and debugging. Kodezi is available as a web-based IDE, a VS Code extension, and an enterprise solution.

CodeMate is an AI pair programmer tool designed to help developers write error-free code faster and more efficiently. It offers features such as code analysis, debugging assistance, code refactoring, and code review using advanced AI algorithms and machine learning techniques. CodeMate supports various programming languages and provides a secure environment for developers to work on their projects. With a user-friendly interface and collaborative features, CodeMate aims to streamline the coding process and enhance productivity for individual developers, teams, and enterprises.

CodeMate is an AI pair programmer tool designed to help developers write error-free code faster. It offers features like code navigation, understanding complex codebases, intuitive interface for smarter coding, instant debugging, code refactoring, and AI-powered code reviews. CodeMate supports all programming languages and provides suggestions for code optimizations. The tool ensures the security and privacy of user code and offers different pricing plans for individual developers, teams, and enterprises. Users can interact with their codebase, documentation, and Git repositories using CodeMate Chat. The tool aims to improve code quality and productivity by acting as a co-developer while programming.

Juno is an AI tool designed to enhance data science workflows by providing code suggestions, automatic debugging, and code editing capabilities. It aims to make data science tasks more efficient and productive by assisting users in writing and optimizing code. Juno prioritizes privacy and offers the option to run on private servers for sensitive datasets.

GiteAI is an AI-powered tool designed to enhance collaboration and productivity for software development teams. It leverages machine learning algorithms to automate code reviews, identify bugs, and suggest improvements in real-time. With GiteAI, developers can streamline their workflow, reduce manual efforts, and ensure code quality. The platform integrates seamlessly with popular version control systems like GitHub, GitLab, and Bitbucket, providing actionable insights and analytics to drive continuous improvement.

SWE Kit is an open-source headless IDE designed for building custom coding agents with state-of-the-art performance. It offers AI-native tools to streamline the coding review process, enhance code quality, and optimize development efficiency. The application supports various agentic frameworks and LLM inference providers, providing a flexible runtime environment for seamless codebase interaction. With features like code analysis, code indexing, and third-party service integrations, SWE Kit empowers developers to create and run coding agents effortlessly.

Harness is an AI-driven software delivery platform that empowers software engineering teams with AI-infused technology for seamless software delivery. It offers a single platform for all software delivery needs, including DevOps modernization, continuous delivery, GitOps, feature flags, infrastructure as code management, chaos engineering, service reliability management, secure software delivery, cloud cost optimization, and more. Harness aims to simplify the developer experience by providing actionable insights on SDLC, secure software supply chain assurance, and AI development assistance throughout the software delivery lifecycle.

CodeScope is an AI tool designed to help users build and edit incredible AI applications. It offers features like one-click code and SEO performance optimization, AI app builder, API creation, headless CMS, development tools, and SEO reporting. CodeScope aims to revolutionize the development workflow by providing a comprehensive solution for developers and marketers to enhance collaboration and efficiency in the digital development and marketing landscape.

ModularMind is a powerful AI assistant application designed to supercharge work efficiency by offering a range of AI-powered features. It allows users to extract relevant content and links from multiple web pages simultaneously, build AI workflows without coding, save prompts, import data, and utilize ready-to-use templates. Trusted by professionals, ModularMind enhances productivity by automating tasks and streamlining workflows.

Office Kube Workflow is an AI-powered productivity tool that offers fully configured workspaces, high degree of workflow automation, workflow extensibility, cloud power leverage, and support for team/organization workflows. It incorporates AI capabilities to boost productivity by enabling seamless creation of artifacts, troubleshooting, and code optimization within the workspace. The platform is designed with enterprise-grade quality focusing on security, scalability, and resilience.

The ZAI is an AI application that offers a platform for generating code files and app structures with the help of artificial intelligence. It provides features such as app structure generation, multi-platform support, code optimization, and rapid prototyping. Users can quickly create functional app prototypes for testing and iteration. The application aims to enhance productivity and streamline the app development process by leveraging AI technology.

VBA Code Generator is an AI-powered tool that allows users to generate VBA code quickly and efficiently. By inputting requirements, users can instantly generate complex VBA code using simple text instructions with the help of AI. The tool is designed for both beginners and experienced users, offering a versatile application that can handle various VBA tasks, from Excel automation to Access database management. With a focus on saving time and streamlining workflows, VBA Code Generator simplifies the coding process and provides accurate formulas for users' specific needs.

Pro React Admin is a comprehensive React admin template that includes features such as theme switching, custom component theming, nested routing, webpack optimization, TypeScript support, multi-tabs, internationalization, code styling, commit message configuration, error handling, code splitting, component documentation generation, and more. It also provides tools for mock server implementation, deployment, linting, formatting, and continuous code review. The template supports various technologies like React, React Router, Webpack, Babel, Ant Design, TypeScript, and Vite, making it suitable for building efficient and scalable React admin applications.

Repopack is a powerful tool that packs your entire repository into a single, AI-friendly file. It optimizes your codebase for AI comprehension, is simple to use with customizable options, and respects Gitignore files for security. The tool generates a packed file with clear separators and AI-oriented explanations, making it ideal for use with Generative AI tools like Claude or ChatGPT. Repopack offers command line options, configuration settings, and multiple methods for setting ignore patterns to exclude specific files or directories during the packing process. It includes features like comment removal for supported file types and a security check using Secretlint to detect sensitive information in files.

LazyLLM is a low-code development tool for building complex AI applications with multiple agents. It assists developers in building AI applications at a low cost and continuously optimizing their performance. The tool provides a convenient workflow for application development and offers standard processes and tools for various stages of application development. Users can quickly prototype applications with LazyLLM, analyze bad cases with scenario task data, and iteratively optimize key components to enhance the overall application performance. LazyLLM aims to simplify the AI application development process and provide flexibility for both beginners and experts to create high-quality applications.

cake is a pure Rust implementation of the llama3 LLM distributed inference based on Candle. The project aims to enable running large models on consumer hardware clusters of iOS, macOS, Linux, and Windows devices by sharding transformer blocks. It allows running inferences on models that wouldn't fit in a single device's GPU memory by batching contiguous transformer blocks on the same worker to minimize latency. The tool provides a way to optimize memory and disk space by splitting the model into smaller bundles for workers, ensuring they only have the necessary data. cake supports various OS, architectures, and accelerations, with different statuses for each configuration.

DB-GPT is a personal database administrator that can solve database problems by reading documents, using various tools, and writing analysis reports. It is currently undergoing an upgrade. **Features:** * **Online Demo:** * Import documents into the knowledge base * Utilize the knowledge base for well-founded Q&A and diagnosis analysis of abnormal alarms * Send feedbacks to refine the intermediate diagnosis results * Edit the diagnosis result * Browse all historical diagnosis results, used metrics, and detailed diagnosis processes * **Language Support:** * English (default) * Chinese (add "language: zh" in config.yaml) * **New Frontend:** * Knowledgebase + Chat Q&A + Diagnosis + Report Replay * **Extreme Speed Version for localized llms:** * 4-bit quantized LLM (reducing inference time by 1/3) * vllm for fast inference (qwen) * Tiny LLM * **Multi-path extraction of document knowledge:** * Vector database (ChromaDB) * RESTful Search Engine (Elasticsearch) * **Expert prompt generation using document knowledge** * **Upgrade the LLM-based diagnosis mechanism:** * Task Dispatching -> Concurrent Diagnosis -> Cross Review -> Report Generation * Synchronous Concurrency Mechanism during LLM inference * **Support monitoring and optimization tools in multiple levels:** * Monitoring metrics (Prometheus) * Flame graph in code level * Diagnosis knowledge retrieval (dbmind) * Logical query transformations (Calcite) * Index optimization algorithms (for PostgreSQL) * Physical operator hints (for PostgreSQL) * Backup and Point-in-time Recovery (Pigsty) * **Continuously updated papers and experimental reports** This project is constantly evolving with new features. Don't forget to star ⭐ and watch 👀 to stay up to date.

Recommenders is a project under the Linux Foundation of AI and Data that assists researchers, developers, and enthusiasts in prototyping, experimenting with, and bringing to production a range of classic and state-of-the-art recommendation systems. The repository contains examples and best practices for building recommendation systems, provided as Jupyter notebooks. It covers tasks such as preparing data, building models using various recommendation algorithms, evaluating algorithms, tuning hyperparameters, and operationalizing models in a production environment on Azure. The project provides utilities to support common tasks like loading datasets, evaluating model outputs, and splitting training/test data. It includes implementations of state-of-the-art algorithms for self-study and customization in applications.

Instrukt is a terminal-based AI integrated environment that allows users to create and instruct modular AI agents, generate document indexes for question-answering, and attach tools to any agent. It provides a platform for users to interact with AI agents in natural language and run them inside secure containers for performing tasks. The tool supports custom AI agents, chat with code and documents, tools customization, prompt console for quick interaction, LangChain ecosystem integration, secure containers for agent execution, and developer console for debugging and introspection. Instrukt aims to make AI accessible to everyone by providing tools that empower users without relying on external APIs and services.

RAG Me Up is a generic framework that enables users to perform Retrieve and Generate (RAG) on their own dataset easily. It consists of a small server and UIs for communication. Best run on GPU with 16GB vRAM. Users can combine RAG with fine-tuning using LLaMa2Lang repository. The tool allows configuration for LLM, data, LLM parameters, prompt, and document splitting. Funding is sought to democratize AI and advance its applications.

LLM-PowerHouse is a comprehensive and curated guide designed to empower developers, researchers, and enthusiasts to harness the true capabilities of Large Language Models (LLMs) and build intelligent applications that push the boundaries of natural language understanding. This GitHub repository provides in-depth articles, codebase mastery, LLM PlayLab, and resources for cost analysis and network visualization. It covers various aspects of LLMs, including NLP, models, training, evaluation metrics, open LLMs, and more. The repository also includes a collection of code examples and tutorials to help users build and deploy LLM-based applications.

This repository contains a comprehensive collection of 63 must-know Large Language Models (LLMs) interview questions. It covers topics such as the architecture of LLMs, transformer models, attention mechanisms, training processes, encoder-decoder frameworks, differences between LLMs and traditional statistical language models, handling context and long-term dependencies, transformers for parallelization, applications of LLMs, sentiment analysis, language translation, conversation AI, chatbots, and more. The readme provides detailed explanations, code examples, and insights into utilizing LLMs for various tasks.

AnnA is a Python script designed to create filtered decks in optimal review order for Anki flashcards. It uses Machine Learning / AI to ensure semantically linked cards are reviewed far apart. The script helps users manage their daily reviews by creating special filtered decks that prioritize reviewing cards that are most different from the rest. It also allows users to reduce the number of daily reviews while increasing retention and automatically identifies semantic neighbors for each note.

Awesome-LLM-Quantization is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements.

The 'create-million-parameter-llm-from-scratch' repository provides a detailed guide on creating a Large Language Model (LLM) with 2.3 million parameters from scratch. The blog replicates the LLaMA approach, incorporating concepts like RMSNorm for pre-normalization, SwiGLU activation function, and Rotary Embeddings. The model is trained on a basic dataset to demonstrate the ease of creating a million-parameter LLM without the need for a high-end GPU.

Generative BI using RAG on AWS is a comprehensive framework designed to enable Generative BI capabilities on customized data sources hosted on AWS. It offers features such as Text-to-SQL functionality for querying data sources using natural language, user-friendly interface for managing data sources, performance enhancement through historical question-answer ranking, and entity recognition. It also allows customization of business information, handling complex attribution analysis problems, and provides an intuitive question-answering UI with a conversational approach for complex queries.

Cortex is a tool that simplifies and accelerates the process of creating applications utilizing modern AI models like chatGPT and GPT-4. It provides a structured interface (GraphQL or REST) to a prompt execution environment, enabling complex augmented prompting and abstracting away model connection complexities like input chunking, rate limiting, output formatting, caching, and error handling. Cortex offers a solution to challenges faced when using AI models, providing a simple package for interacting with NL AI models.

Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. It is designed to format your codebase for easy understanding by AI tools like Large Language Models (LLMs), Claude, ChatGPT, and Gemini. Repomix offers features such as AI optimization, token counting, simplicity in usage, customization options, Git awareness, and security-focused checks using Secretlint. It allows users to pack their entire repository or specific directories/files using glob patterns, and even supports processing remote Git repositories. The tool generates output in plain text, XML, or Markdown formats, with options for including/excluding files, removing comments, and performing security checks. Repomix also provides a global configuration option, custom instructions for AI context, and a security check feature to detect sensitive information in files.

RAG Me Up is a generic framework that enables users to perform Retrieve, Answer, Generate (RAG) on their own dataset easily. It consists of a small server and UIs for communication. The tool can run on CPU but is optimized for GPUs with at least 16GB of vRAM. Users can combine RAG with fine-tuning using the LLaMa2Lang repository. The tool provides a configurable RAG pipeline without the need for coding, utilizing indexing and inference steps to accurately answer user queries.

The LLM course is divided into three parts: 1. 🧩 **LLM Fundamentals** covers essential knowledge about mathematics, Python, and neural networks. 2. 🧑‍🔬 **The LLM Scientist** focuses on building the best possible LLMs using the latest techniques. 3. 👷 **The LLM Engineer** focuses on creating LLM-based applications and deploying them. For an interactive version of this course, I created two **LLM assistants** that will answer questions and test your knowledge in a personalized way: * 🤗 **HuggingChat Assistant**: Free version using Mixtral-8x7B. * 🤖 **ChatGPT Assistant**: Requires a premium account. ## 📝 Notebooks A list of notebooks and articles related to large language models. ### Tools | Notebook | Description | Notebook | |----------|-------------|----------| | 🧐 LLM AutoEval | Automatically evaluate your LLMs using RunPod |  | | 🥱 LazyMergekit | Easily merge models using MergeKit in one click. |  | | 🦎 LazyAxolotl | Fine-tune models in the cloud using Axolotl in one click. |  | | ⚡ AutoQuant | Quantize LLMs in GGUF, GPTQ, EXL2, AWQ, and HQQ formats in one click. |  | | 🌳 Model Family Tree | Visualize the family tree of merged models. |  | | 🚀 ZeroSpace | Automatically create a Gradio chat interface using a free ZeroGPU. |  |

Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. It is a systematic & reusable library of 80+ core OPs, 20+ reusable config recipes, and 20+ feature-rich dedicated toolkits, designed to function independently of specific LLM datasets and processing pipelines. Data-Juicer allows detailed data analyses with an automated report generation feature for a deeper understanding of your dataset. Coupled with multi-dimension automatic evaluation capabilities, it supports a timely feedback loop at multiple stages in the LLM development process. Data-Juicer offers tens of pre-built data processing recipes for pre-training, fine-tuning, en, zh, and more scenarios. It provides a speedy data processing pipeline requiring less memory and CPU usage, optimized for maximum productivity. Data-Juicer is flexible & extensible, accommodating most types of data formats and allowing flexible combinations of OPs. It is designed for simplicity, with comprehensive documentation, easy start guides and demo configs, and intuitive configuration with simple adding/removing OPs from existing configs.

I test and optimize your code snippets.

A Senior Developer AI Assistant for optimizing and debugging code.

优化代码，提升运行速度的专家

First discusses assistant details, then implements tailored code solutions.

我分析并优化代码以提高性能和可读性。

Your own personal senior software engineer mentor critiquing and optimizing your code helping your improve.

Code-formatting and optimization assistant.

Refines code in multiple languages.

Code helper with CSS styling for ASP and HTML.

AI and code optimization expert in Mojo

Front-end dev expert, adapting to your code style

Custom GPT for Python Experts: Elevate your code with AI-driven optimizations, advanced debugging, and the latest Python trends. Tailored for seasoned developers, it's your key to mastering Pythonic best practices.

Assists with Qiskit code and quantum computing concepts.

Refactor python code. Python expert with proficiency in data science, machine learning (including LLM apps), and both OOP and functional programming.

Analyzes code for time and memory complexity

Elevate your PHP programming with AI-guided support. Need expert insights, bug resolutions, code optimizations, or upgrades? PHP Mentor delivers custom assistance for developers across all expertise levels, making coding simpler.

Specializing in Web Development, Apps, Dev Tools, and SaaS. Python, TypeScript, JavaScript, HTML, SCSS. Fluent in Angular, Vue, React, Svelte, Webpack, Vite, Vercel, Next, Nuxt, SvelteKit, Node, GO, PHP, C#, AODA and WCGAG 2.1. Code is the way.

Expert in Vue 3 and Quasar Framework, focused on quality code.

为你写代码或者提供代码建议优化

帮助编写代码